I saw someone else did something like this recently and thought that I might have something to add to the discussion to help people figure out whether they think this program is right for them, or for people currently in the program to help them plan out classes.
My background is very heavy in statistics and finance (I'm an actuary), so my grounding in calculus, statistics, linear algebra, and business topics was considerably better than most of the other people I interacted with in this program. Conversely, I'm sure my programming skills were probably about average or maybe a little bit below compared to someone with a more targeted background towards those skills.
I started in Fall of 2020 and just finished up this month, Spring 2024. I started out just taking one class a semester and never changed up that plan, would highly recommend doing the same if you're working full time alongside; there's no reason to rush this program. I got a 4.0 GPA overall, although I never really stressed that much about it and definitely did not shy away from "harder" classes in order to bolster GPA. I did this to learn, not to get good grades. The classes I took, in order (my memory of some of the earlier ones might be a bit jumbled as so much time has passed):

1. CSE 6040 - I mentioned how my programming background was weaker relative to my mathematical background. However, reflecting on my experience in this class, it was probably still pretty strong. This class is focused on generalized programming skills, you don't really get into the analytics and modeling that much; it's more of a primer on things like functions, recursion, computer memory management, etc. It's been a few years, but I don't remember struggling with this class at all, and most of the concepts covered (object oriented programming, things like byte encoding, hexadecimal forms, recursion, etc.) were things I was already familiar with in another programming language (this class was in Python) or was relatively easy to pick up. From what I remember, the assignments were auto-graded and you had unlimited attempts, not to mention the fact that most of the prompts were to produce some predetermined result... and, as long as you were able to verify that your code produced that result, you got full points. I didn't miss a single point in this entire class. I believe there were "final exams" which were really just timed window coding assignments much like the homework, and you could do the assignments at any point during a 4-day window or something like that.
2. ISYE 6501 - This class was R-based and focused on basic analytics models. The material was much more applied than 6040. Similarly, the material was not difficult, and I was familiar with a lot of the basic models already (such as GLMs) from having worked with them in my job. The grading was done on a peer-grading framework; based on who anonymously is assigned your homework to grade, you can get someone who's a stickler for every point on the guide, or people who are a bit more lenient. I never really worried much about how things were graded in this class; yeah, I did miss some points arbitrarily, but nothing that made that much of a difference. If you generally put in the work and understand the material, your peers will recognize that. I found this a bit more interesting than 6040 because, rather than a deterministic "right answer", there was some more creativity implied here to solve each problem. There was a final project for this class where you walked through a hypothetical analytics problem and explained how you would go about solving it. I found this an interesting thought exercise and enjoyed this class. The pacing felt a little fast, as you basically had an assignment due each week, but the assignments were small. Like 6040 I found this class to be quite easy but I didn't 100% it due to the peer grading thing.
3. MGT 8803 - I almost applied to be exempt from this class, as my background intersects a lot with the material. The accounting and finance modules for this class literally did not teach me anything new. Supply chain was new for me and I found it interesting. I'm trying to remember what the other module was. I think it was marketing? I didn't like it. Overall I found this class quite easy for the aforementioned reasons, however I've heard from a lot of the other folks without business backgrounds that this class was pretty tough so take my opinions with a grain of salt. Taking this in the summer cut out one of the modules, normally there are 5 but in Summer there are 4. I figured this made sense to take during the truncated semester because I was unlikely to cover that much new material, and it turns out I was right about that. Each module lasted 2 weeks (I think in a normal semester it lasts 3) and has a timed multiple-choice test at the end. A lot of people didn't like this format compared to ISYE 6501 and CSE 6040; I'm not really sure how else this material could've been covered. This class was OK, the material is not really that deep but it's a pretty good primer on a large number of business topics.
4. ISYE 6740 - The first class I took that was actually pretty challenging, which makes sense considering the first 3 courses were just the basic core. This is pretty much an intro to machine learning as a discipline, and the first time I remember digging into academic papers that discuss some machine learning topic and attempting to recreate the results (this is something we did a lot in the more advanced classes going forward and incidentally now that I have graduated is probably one of the best ways to go about learning a new topic). I remember this class as having a format similar to ISYE 6501/CSE6040 in that you had large programming assignments to do, as well as open-book "exams" which were really just timed programming assignments. Assignments are not auto-graded; TA's review each one and thus the assignments have much more of a focus on explaining your findings than producing the exact expected output (unlike 6040). Some of the theory questions have you applying complicated matrix algebra rules that I'm not surprised a lot of people struggled with. The TA responsiveness in this class was pretty good from what I remember, but your mileage may vary. I remember getting 3 weeks to do each assignment but I also remember not thinking that was a lot of time, these assignments are very extensive, have many parts, and take a long time to get through. Like with 6040 I ended up not missing a single point in this class but I did find it difficult and spent significantly more time working on it than in prior classes, probably 10-15 hrs a week, give or take.
5. ISYE 6644 - I was familiar with maybe 50% of the material we covered due to my extensive statistics background, however I was not aware of the exact mechanics of random number generation or the concept of a batched mean, for example. I remember this class having several "check your understanding" quizzes that focused on the mathematical foundations. Didn't struggle with this much in terms of difficulty and found the material very useful. Setting up custom simulation environments is very useful and arena is pretty cool even if it's unlikely you'll ever use it. Some assignments feature similar tools in Python (simpy). There might have been some coverage of R in this as well, or at least the accommodation for people that wanted to use it. There was a project for this class, but you didn't have to come up with the topic on your own, you could pick from a list, and you could do your project on your own if you wanted (which, given the option, was always the choice I made, due to the inherent randomness in picking the right members of a group). However you can do a group project if you want.
6. MGT 6203 - The first of the classes I took that required a group project. I recommend you are proactive in putting together groups in situations like these, posting threads on Ed/whatever the forum is as soon as the class begins. My group was alright; not everyone in it was great, but we had enough going overall to make up for the weaker group members. The project has some arbitrary guidelines from what I remember - you need to put together a midterm report and video presentation that is no more than ~2 minutes long or something like that (if it's 2:01 you get penalized) and the final report is 5 minutes or less, and everyone in the group needs to speak. I honestly don't remember much else about this class, it was pretty forgettable, but not horrible. Not overall that difficult, another business class so a lot of topics I was already familiar with, but there was more new here than in 8803.
7. CSE 6242 - Another class with a group project. Again, I was proactive, and again, overall, my group was... okay. Some people who were really good, some who were... not. This class is characterized by a lot of assignments that are autograded, like 6040, but the assignments are a bit more difficult. Overall not that difficult with the exception of the D3 assignment, but that's more due to the fact that I'm not really sure how the autograder works for that; it tries to determine based on some internal structure of your html code whether or not you're fulfilling the requirements. I got a perfect score on all of the assignments, and they give you the chance to score over 100% on I believe either assignment 1 or assignment 2. A lot of people bombed the D3 assignment (I think it's assignment 2) but still did well in the class because it's not that hard to do well on everything else, so keep that in mind. This class does a great job of exposing you to a lot of new technologies, but there isn't that much depth to it. That's not really the point of this kind of class though, it equips you with the tools to explore things deeper if you so choose.
8. ISYE 8803 - I was a big fan of this class. It's taught in MATLAB but you can use Python if you so choose, you'll see in reviews of this class that you should really just use MATLAB since a lot of the sample code etc. is not in other languages, so that's what I did. However, they must've recently added Python and R code for sample solutions, so feel free to use what you want. MATLAB was interesting, there were parts of one assignment I also used R for (grouped lasso in R is a lot more straightforward). This class is all about high dimensional data and representing it in a more simplified and comprehensive way, think about something like sonar which might have datapoints separated by milliseconds and thus a very dense representation of a signal captured over a short period of time. After ISYE 6740, I found this to be the class that taught me the most up to this point.
9. CS 7642 - Taking this class in summer is kind of rough. There's 6 homework assignments that are autograded, similar format to CSE 6040. There are 3 projects which are much larger programming assignments for which you'll write papers explaining methodology, results, etc. These projects take a while, particularly project 3. I did well on projects 1 and 2 and decently on 3, although I spent the most time on 3 by far; it involves reinforcement learning to simulate a soccer environment and train agents how to play against an AI developed externally. The AI baselines are hard to beat, and I didn't manage to beat them, but I wrote a decent paper explaining what I did. The final exam for this class should be dropped as it doesn't add value to the class, people regularly score extremely low on it, the average score in the class was something like a 45%. I scored a bit lower than average but still got an A in the class because it was heavily curved. Reinforcement learning is a very interesting topic, though, and I would highly recommend this class as a primer on the material. It's probably a good idea not to take it in the summer, though.
10. CS 7643 - This class was pretty difficult but I still think 6740 was tougher. The material is extremely dense. There are parts of programming assignments that are autograded, but also short answer portions that are reviewed by TAs. Grading on those were pretty subjective. This is the only class I can remember really needing to discuss things with TAs to understand what was being asked a little better. Unfortunately, the TAs in the semester I took this weren't the best. They seemed more concerned with unintentionally giving away a bit too much information in any of their responses. I can understand this, but it came off as intentionally opaque most of the time. There was a group project for this course as well, and my group was excellent, probably the best experience I had with a group in this program. I can imagine how much this course would've sucked if I would've had a mediocre/bad group. Based on discussions with my group, some of the grading seemed highly arbitrary, with some TAs grading similar responses to the same question differently. Like I said above, though, I never really worried about this. I never once in this program ever disputed a grade, and I continued with that in this class as well.
11. CSE 6748 - Practicum and final class. For this class you get to choose between a number of pre-determined Georgia Tech sponsors, or form your own project for your own employesome external entity. It was a lot more work to do this, so I just went with one of the pre-determined GTech ones. I really enjoyed this one, I had constant communication with the sponsor as I developed my project and came up with something that I was quite proud of. I wanted to explore a natural language processing task, so I picked a project that I thought would allow me to do this, and was very satisfied with the result. There's a number of videos you have to watch that explain some overarching aspect of analytics that were pretty interesting as well, you can watch all of these in a single day and then focus on the project if you like. It's possible to finish the entire semester's work in just a few weeks, I was able to do the entire project and write the final paper in about a month's time, at which point I coordinated with the sponsor to tailor the work I did to a format that they would be able to implement for their business problem if they wanted to.

I can't comment on the job placement prospects of this program, as I just finished it and was actively employed the entire time I was in it. As an actuary there's not much this program does that my exam certification process didn't in terms of career prospects. However, it did position me much better within the context of the expanding role of data and analytics in insurance going forward, and also opens me up to similarly mathematical roles with a firmer grounding in big data and also some business elements (quantitative finance/data science roles). There were also things I learned in this program that I was able to apply directly to my day-to-day work. If you're considering this program, I would recommend you think about a few things:

1. I'm pretty shocked at how many people I saw during my program who didn't really think that much about why they're doing this. I get that the barrier to entry is low, but it's a serious commitment if you're actually trying to graduate. Most of the people who start this program don't finish, so consider whether you're ready to spend almost 4 years going to school part-time, or if you're able to double up on classes for some of the semesters. Most of the people I know in the program doubled up at least once, I never did but I was never in a hurry. If you must double up, don't make it your first semester. Dip your toe in the water, see how it is, and then reassess. But, above all else, think about why you want to do this, and use that as your guiding goal to bring you through to the end.
2. Something I tended to see pretty much without fail in most of my classes - a lot of the graduate students in this program spend way too much time worrying about minute, particular details that don't really matter. Maybe it was just my philosophy that I would probably never dispute a grade, or that I was never really that concerned with getting a perfect GPA, etc. but I was always marveling at what I saw asked in Ed posts. People would ask whether they could use a certain programming language for an assignment, what packages they were allowed to use, would post screenshots of bugs and ask for TA's to help walk them through it, etc. Generally, without fail, the TAs would respond along the lines of: use whatever programming language you want, as long as you can display your output/submit it in a way that we can verify by running ourselves, we'll make the effort; use the debugger to step through your code to find the problem; etc. Generally, in most cases, the assignments and questions are designed in a way to teach you something, to get you to realize/understand some pattern or data concept that has some underlying logic that makes sense. For example, the idea of saliency maps on image processing takes the 3-channel RGB color pixel shading representation of an image and condenses it into a single channel, and, as a result of that, loses some resolution in suggesting parts of the image driving a model result that might be different depending on the channel; i.e., an image with a very heavily blue-shaded part that detracts from a certain result, but with a red-shaded part somewhere else that increases the probability of the modeled result. This was part of a conceptual question on how saliency maps differed from other pixel influence attribution methods in Deep Learning, and is part of what you should logically understand since it reduces the channels of the image representation from 3 (R, G, B) to 1 (usually grayscale). I think people tend to run to the TA the second they have difficulty with something and don't stop for a second to think it through, one exercise I might recommend is to consider: if you ran into this problem out in the world and you didn't have a TA/managesome other authority figure to explain the answer to you, what do you think it might be? Does the answer even matter? If it still matters and you have no idea how to solve it, maybe then you can go to the TA.
3. In every single group project I worked on, we had an initial planning session where we determined the scope of what we wanted to do. For most of the projects, this was an essential deliverable in addition to the final paper. However, in almost every case, someone in the group was always playing some game of runaway scope where they kept on wanting to add methods/questions to exploration beyond what was initially planned in ways that I intuitively knew would be impossible to manage in just one semester. I often had to say something along the lines of "if we have time we'll do that" or "when we write up our paper, we can put that in the avenues for future exploration section" or something similar. It turns out that we never had time to look into these things, and our initial scope was usually well-defined considering the time we had. I'm not sure why this was always so front-and-center in my focus, maybe since I used to work in consulting and project budgeting/scoping is so unbelievably important in that context. Whatever the case may be, understand that you won't be able to change the world every time you do a project. Make some incremental improvement, reflect on the results, and then include some notes in a "potential avenues for future exploration" section. I was pretty surprised at how many people had so much trouble putting the pencils down at the end. I can practically guarantee that, for the classes where I did a project on my own, I probably did substantially less work than other individual groups for precisely this reason. In general, you probably don't have to do as much work as you think you do.

So, would I recommend the program overall? Absolutely. It's not perfect, I found some of the formats annoying - CS 7642 has no business having that final exam, it adds nothing to the class at all, is arbitrarily extremely difficult and the class is good enough and complete enough with the removal of that exam that its inclusion to me appears to be the result of some arbitrary quota somewhere. I also don't really like the group project format and profoundly disagree with the reasoning that GTech and most other academic institutions give as to why group projects are even good or necessary, however I do acknowledge that from a logistics and resource standpoint it's unmanageable to grade individual projects for every single person in a given class and group projects do decrease the number of papers that TAs will have to read. Considering the scale of what GTech has managed to do, and how many students enroll each year, I'm surprised the program is as well-managed as it is. Yes, it does require a lot of self-teaching, but in most cases you can actively engage with TAs multiple times a week if you're struggling with topics and from what I've seen they were very responsive.
Anyways just wanted to give my perspective as someone who just finished this program and still thinks it's worthwhile despite its flaws.

Hi
I'll preface by saying my experience is limited to building 2 personal pc's, tinkering with fan/clock speeds, and basic folder sharing between Windows pc's at home. I've never used dockerfiles or linux so far.
The last few weeks I've been trying to read forums and posts, and watch as many guides and explanations as possible to help get my first understandings of home servers. I've reached a point where I am tipping into overwhelmed with possibilities (probably overthinking), and struggling with how I proceed.
I think I'm mostly struggling with how it all connects and how/what software I need to make it easily remote accessible/a cloud server, so help on this front would be great. Thanks in advance.
First idea: I use my Old PC + new HDD's as the servecloud hardware. (Cheaper and ideal in that it uses old parts)
My understanding so far for this is;

1. I reset the Win 10 operating system on my Old PC
2. Remove Win bloatware
3. Set new HDD's to Raid 5 and format
4. Install Plex media server
5. Install Steam with games
6. Install Moonlight/Sunshine for streaming Far Cry 6
7. Install Immich or Photosync with Photoprism for auto photo backups from mobile phones
8. ?Designate folder access for other users on the local network?
9. Tailscale vpn for remote access (never used it before)
10. ...unsure if i need to do anything else

Second idea: Buy a Synology device and add HDD. This acts as media+photo+file servecloud and remains on 24/7. Old PC gets turned on intermittently to act as GUI for Web browsing+PC gaming on TV. (upfront more expensive, possibly easier to first setup)
Below are some parameters of what I'm trying to do/use.
Functions to perform:

1. Connect to tv, other pc’s and mobile devices within local home network for access to personal media (movies, music, photos).
2. Storage of home media, personal documents
3. Access to web browsing on TV for ad-free viewing instead of using direct aps like YouTube (I imagine i need a GUI for this such as Windows 10)
4. Infrequent pc gaming on TV (without using my gaming specific pc to stream from. Far cry 6 on low-ish settings but OK fps).
5. Auto backup/syncing of photos from Mobile phones.
6. Avoid needing to use public cloud services like Google Photos/Apple iCloud/Microsoft Onedrive as file sharing/backup/remote access.
7. Be online and accessible 24/7

Note: I’d welcome any tips to reduce noise and wattage profile.
Room layout:

• Room 1 has - Router, TV, Nvidia Shield Pro
• Room 2 has - Gaming PC, space for home server device and/or additional hardware device.

Planning to buy so far:

• 4 x Seagate IronWolf Pro 16 TB 3.5" 7200 RPM Internal Hard Drive

Hardware I have:

• Display: TCL tv 43P6US (4k UHD 3840x2160) (HDMI + ethernet port)
• With TV: Nvidia Shield TV Pro
• Router: TP Link Archer 1600v (1600Mbps total wifispeed, 1300Mbps on 5GHz)
• Internet provider connection: 55/20 Mbps down up
• In-home net connection: 5g wifi, 600AV2 power line (600 Mbps)
• Router sits with TV+Shield Pro, keyboard+mouse, xbox controller
• Phone: iPhone 13, Samsung Galaxy (5yr old)

(Old PC part list)

• CPU: Intel Core i5-8600K 3.6 GHz 6-Core Processor
• Mobo: Asus Prime Z370-A ATX LGA1151 Motherboard
• RAM: Corsair Vengeance LPX 8 GB (2 x 4 GB) DDR4-3000 CL15 Memory
• Storage: Samsung 860 Evo 1 TB M.2-2280 SATA Solid State Drive
• GPU: EVGA SC GAMING ACX 3.0 Black Edition GeForce GTX 1070 8 GB Video Card
• Case: be quiet! Silent Base 800 ATX Mid Tower Case
• CPU cooler: be quiet! Dark Rock Pro 3 67.8 CFM Fluid Dynamic Bearing CPU Cooler
• PSU: SeaSonic Focus Plus Gold 550 W 80+ Gold Certified
• Wifi: 5GHz
• Operating System: Microsoft Windows 10 AAOEM

Hey there! I recently decided to play Enderal Forgotten Stories on Steam Deck, to scratch that yearly Skyrim nostalgia. However the gamepad controls felt awful and so did rebinding everything as mouse and keyboard.
After some tinkering I managed to get a very comfortable setup, and I wanted to share a quick guide in case anyone is interested. For those that dont know, Enderal is free on Steam if you own Skyrim, which I still find insane (it even plays like a standalone game).
This setup allows you to use joystick, trackpad and gyro as mouse, while still utilizing gamepad controls. In my opinion this is the most comfortable way to play, but its impossible by default. It also adds a radial menu on the left trackpad for 8 favorite slots.
Requirements: - Own Skyrim Special Edition (this method works specifically with the Special Edition version, haven't tested on others). - Open the game, go to settings, gameplay, and allow gamepad/controller. - Download "Auto Input Switch" (version 1.5.97, otherwise it doesnt work with Special Edition) from Nexus. - Download "Address Library for SKSE Plugins" From Nexus.
Installation Steps: - Open desktop mode - Download the previous requirements from Nexus manually. - Extract the contents of both, I recommend creating a new folder, moving both inside, then selecting both, then "extract here". This should create a new folder called "SKSE", another folder withing called "Plugins", and inside all the files that we need. - Locate the game folder. Should be something like "..... /steamapps/common/Enderal Special Edition" - Navigate to the "Data/SKSE/Plugins" folderiand make a copy of the contents just in case. - Add the extracted files directly into the game's "Plugins" folder (do not include the folders, just the files). Accept any override. - Go back to gaming mode.
VERY recommended: - In the game launcher, make sure mouse sensitivity is set to the lowest. - Setup the controls. Search for my control layout in the Community Layouts, named "Perfect Steam Deck customized controls" by Renoviejo.Select and apply it.This setup significantly enhances the gameplay in my opinion, mimicking the configuration I’ve been using for about 90 hours in my Viva New Vegas playthrough. It combines the precision of a mouse and the convenience of gamepad controls, making your Enderal journey much more enjoyable.
Thats it! I hope I didn't forget anything and that this is useful for someone. Enjoy :)

I have no car and will be getting one early next year. I currently have very good credit (<750) and a small bundle in a hysa.
I am considering taking a 0% apy credit card offer to put my usual expenses that would normally have come out of income + savings, onto an interest-free account, to let the money instead accrue interest in my savings. Then pay all of the debt before credit card interest kicks in, and pocket the hysa interest.
However, I'm unsure if the hysa return per month would outweigh the possibly heightened interest rate on the auto loan that I will be taking soon, as caused by the temporary credit score loss due to a new account.
Is there any way I can estimate how much of a change in credit score a new account would cause, and/or what interest rates I might expect on an auto loan?

Time Stamp
https://imgur.com/a/M7QAbGz
NO TRADES PLEASE.

1. SPK lamia gen 2 cruwear. Second owner. I disassembled, completely cleaned, re-lubricated with non-fluorinated lube, tuned the pivot to be flickible with no blade play, and applied blue Loctite. Comes with a purple anodized pivot that I didn’t care for. Also comes with alternate polyurethane washers. Knife is in perfect shape and comes with pouch and sticker. Never sharpened, carried once. Centered. SV $700

https://imgur.com/a/OCB5Vbg

1. Benchmade mini cricket crooked river. Bench made custom shop with carbon fiber, scales, copper pivot, S 90 V. like a lot of bench maids, this one was not centered. In the process of disassembling to correct this, which I’ve done many times with benchmades I stripped a t6 screw near the blade. All other screws were them near the blade. All other screws were them replaced with titanium screws were then replaced with titanium screws. However, blade is now perfectly centered, action is very good. Never sharpened. Carried once.

No scratches or dings. I miss placed the box, but comes with the blue pouch.
SV $180 obo
https://imgur.com/a/SwNX18r

1. Pena X Mula with sheepsfoot m390 and micarta inlay. Production model manufactured by Reate. Extremely smooth action and drop shut. Never disassembled. Touched up on ceramic. This one was carried quite a bit with some scratches on the milled titanium clip, but the blade and handle are in excellent shape, like new. This one comes with the box and cleaning rag.

SV $225 obo
https://imgur.com/a/6kHZxj7

1. Chaves RCK-9 production model. Full titanium. M390. Comes with skull clip and box. I am the first donor, carried once. Never sharpened. Perfect action.

SV $250 obo
https://imgur.com/a/eEodAep

1. We Esprit. 20cv with flamed titanium handle. This one was also carried moderately and has some snails on the titanium anodization. Blade is perfect, action crisp, drop shut. Touched up on ceramic. Never disassembled. This one does not come with the box.

SV $175 obo
https://imgur.com/a/tRe5mTI

1. Asher spiro acuto I’m s35vn. Comes with pouch. Never disassembled or modified. Carried <3x

SV $115 SOLD
https://imgur.com/a/wiOVYyN
All prices are slightly negotiable. Anyone who bundles two or more will get a free Land Small Sebenza Clone in S 35 VN that has a light scratch on the blade, pics available at request. No, this is not for straight up sale.
All will be shipped USPS priority. PayPal only. YOLO trumps all.

First of all, let me clear out a few things.

• I'm not a stan of any contestant and I'll try not to have a bias towards anyone while i post this.
• I'm not criticising anyone for their looks or weakness but mostly for their hypocritical actions & words which is negatively impacting the show and majorly spoiling the vibes.
• I know this is gonna be long, i might miss out a few points which you can add in comments , so please bear with me.
• Mods, I'm not breaking any rules or abusing anyone here. Just stating my observations.
• I'll state the good points too which i like about everybody. The negatives & the positives keep changing with every epsisode. So this is limited to what is up so far.
• I'll keep the content limited to what i see in episodes as i don't follow the recent insta controversies much.

Siwet : - Avoids situations & conversations and try to divert any actual blames with some past stories or fake sympathies. - Always up for fighting people in dome and get aggressive which is sooo overdone. - Let Anica speak ffs! - Call yourself a "performer" only when you actually perform ! - "Addy tune baakiyo ko pitch ki toh tujhe nahi liya" Wtf bro ?

• He tries to respect bonds, goes on a limb to save Aniket & Ayushman as much as he could. Did addy dirty a couple of times though.
• Although everybody plans and plots, but plays game on face more than other contestants rather than hiding behind.

Anica : - Stop victimising yourself so much that your emotions start looking washed out. - Grow out of the dependant personality. - "Brooo" and the 🤌🏻🤌🏻 are irritating af.

• Haven't fucked up any task as such.
• She doesn't bitch any wrong things about Lakshay and tries to maintain good relations which i find nice.

Digvijay : - Stop with the hypocrisy! "Mai toh bolunga beech me" & "mere beech me mat bol" is plane stupid. - Although all ex-roadies & TRP contestants are getting majorly favoured, but his looks very clear with the out of nowhere saves & unfair ideal match contender when he was literally standing unsafe. - Stop using your friends (nayera to save, then demotivating her for dome which was logically right but could have been said subtly) (Gullu to write his name and then dumping her) (Akriti to save him and not sending her to den which i really loved tho XD ) - However true it maybe as well know, but calling out Prince to de-justify any other's spot was just purely out of jealousy and spite when he literally tried to do the same in roadies and outside.

• Plays game straight forward out of all the others. No behind the back bullshit.
• Beast performer
• Good at logics and strategies (asking Nayera not to go to the dome which almost eliminated Sachin if not for the twist) ik i contradicted myself but he could have talked it out better.
• Never said anything wrong about his ex.

Unnati : - although almost all the couples are fake and were pre-planned but having a bf outside and still coming to the show is a big NO NO ! - stop being so insecure dragging ishita in everything needs to stop when digvijay & ishita are literally showing no affections to each other (although i get the emotions & bringing exes was the whole point of this but still) - Crybaby over having no friends what?!

• Chose a good partner is all i can say lol.

Addy : - STOP flexing your steroids , losing temper every two seconds. - Grow a spine, "mai kabhi task nahi karunga iske saath" to "meri marzi mai jo karu"

• Might turn out to be a good performer in strength based task, haven't had any yet.
• Having survived so far and would survive further which is expected despite being all this stupidity, I'll count as a plus idk xD

Kashish : - Stop being so horny all the time ffs, it's soo cringe. - This fake sophisticated queen aura needs to be stopped.

• Doesn't fear to call out people . Be it akriti , yuvraj or even his own connection sometimes.
• Good performer so far.
• vamp vibes me likey.

Lakshay : - Same as unnati, having a gf and coming to the show is a NO NO for me. - Again like addy, stop making diggy papa and grow a spine. (Asking for chances to save and then giving them to diggy taking others for a fool) - However bitter your past relation maybe, but don't let Diggy disrespect your ex infront of you or everyone when you say you respect her. - Speak more bruh.

• Most well mannered among any other guy. Calm minded, lets people speak to the point of literally getting walked over.
• Haven't spoke shit about any people in the game.
• Supports his friends.

Ruru : - Unneccessary baseless shouting in last dome was such a turn off exactly like Divyansh.

• Tough mentality.
• Nice vibes , cute.

Sachin : - Literally a dumb character, lost half of the times, fucks up tasks . - cries more than needed ( he was done dirty in the court room tho) - Confused with connections and goes for the ones which makes no sense ( like deekila who was already messed up with aniket & even the personalities are so poles apart) . good that he finally paired up now. - Either defend your connection or just call her out for her fuckup, don't try to play both sides. (court room digvijay i love you drama)

• Genuine overall. Tries to maintain good relations with everyone and does less groupism than other people.
• Sweet & gonna rock in dance & entertainment & town-market wale tasks (if there any) probably.

Akriti : - Most cringe contestant of the whole show. - Majorly favoured by the show be it ideal match or screentime or VDs. - Crybaby max. Cry over sachin, cry over diggy allegations, cry over not being able to go to Loveden, cry over people calling her put and i can go on. - stop speaking in between everybody ffs. (she does it way far more than siwet & diggy) - Stop acting like a queen ffs it's so cringe. - stop with your "Maine aapko favour kiya aap mujhe favour lautao" . mat karo bhai favour fir . - Acts like a mastermind by saving diggy and then crying about it and bringing it up everytime.

• favours friends which is good in splitsvilla ig? (throwing hearts wala task where everybody was trying to show themselves neutral just for screen)
• understands vote in , vote outs and numbers game a little better.

Jashwant : - Stop with haan-ji, correct , ekdum sahi, bilkul, agreed and have your own opinions. - Stop with the cringe romantic one liners . - Speak more bruh (but speak sensible) and speak for yourself. You're not your partners' ambassador.

• Good genes lol
• Laidback, chill.

Nayera : - Stop milking your 2 day fling for such drama and sympathy (although it was need of the show and she finally got over it but still) - Stop crying and showing how you got hurt & ruined and then call it chewing gum and stuff. double standards.

• Goes out on a limb for friends. Values relations over playing double sides.
• Beast performer.

Harsh : - Most cringe contestant after Akriti. Stop with this King-Queen bullshit. - Stop acting like you're playing neutral when you're actually playing both sides (dono side jaake chugli karna) - Stop hyping up yourself as morally correct using feminism and fairness. (court room , tasks and dome votes)

• Somehow gets the best girls wtf

Rushali : - What a poor choice of guy lol - Elegant. Well behaved. Carries herself well. Dresses beautifully and talks graciously.
Shobhika - Again, having a bf and coming to the show ? NOPE. - Cried when called out by yuvraj and legit ran away from the set? - Does nothing and is basically female ayushman lol.

• somehow has the best friends to save her everytime.
• chill, laidback, cute .

Ishita : - Going and fighting to stand between Diggy and unnati in ex-isle was so weird to watch (although she was been told by uorfi)

• Nice personality overall. always respects diggy and never bitches about him.

Yuvraj : - Does he really understand the concept of the show? You have to make a connection to move forward lol.

• Dresses cool. Genuine and great personality and styling sense.
• Most chill and laidback (after lord Rigden ofcourse)

Adit : - Please grow a spine and stop having a herd mentality. - not fit for the politics and the dirties of the show.

• Great vibes, pretty chill, funny.

Khanak: - Stop following the herd mentality again. - Despite even knowing the other connections are fake and theirs are genuine, it somehow seems faker than the others?

• Carries herself well.
• Gives proper sophisticated NRI vibes (unlike kashish & shobhika. idk if they're for sure)

Ameha : - Idk. speak more? hide less. - Cutest of all. Dresses and carries herself well. - Most bearable nepali contestant amongst all. (it has nothing to do with race. it just how she carries herself better than the rest)
Devakaran : - speak more , hide less in crowd maybe ? - Old school gentlemen vibes.
Arbaaz : - Being married and coming to the show? NOPEEEE. - Romance is so dead and fake . cringe.

• No drama . Speaks as much needed and somehow still not hides in the crowd and have a more opinionated stand than adit & devkaran.

Aniket : - Major toxicity alert! Messed up relationship, mean vibes and much controlling. - Maintains calm even when provoked . Tries not to involve people in his messed up connection (his fuckups actually) .
Deekila : - Dependant personality pro max. - Irritating to the ears once she starts shouting. - Forgiving aniket after whatver was revealed to us is the only truth takes heart and if she takes step to fix it , it's heartening to see. (although it's toxic and wrong but still)
Lastly, i feel like this calling out was much needed. Akriti hate on this sub is justified, Digvijay worshipping is going too much and needs to be called out for his hypocrisy but i think is this sub is filled with his insta supporters now, dewangini-divyansh stupidity was needed to be called out for, ayushman and rigden hype is a yesss, nayera is underrated and siwet turns his unneccessary hate into completely neccessary with each episode and instagram oustide the show . Sorry, not sorry. Feel free to add any if i missed or you don't agree to.

Everything in my inventory is up for trade. The most valuable items are listed here, the rest you can find in My Inventory

Feel free to Add Me or even better send a Trade Offer. Open for any suggestions: upgrades, downgrades / knives, gloves, skins / stickers, patterns, floats.

All Buyouts are listed in cash value.

KNIVES

★ Butterfly Knife Lore (Factory New), B/O: $7194.77

★ Butterfly Knife Autotronic (Minimal Wear), B/O: $2025.74

⎯

★ M9 Bayonet Ultraviolet (Field-Tested), B/O: $557.87

★ M9 Bayonet Stained (Well-Worn), B/O: $529.41

★ M9 Bayonet Boreal Forest (Field-Tested), B/O: $465.39

⎯

★ Talon Knife Doppler (Factory New), B/O: $1295.27

★ Bayonet Tiger Tooth (Minimal Wear), B/O: $746.28

★ Karambit Bright Water (Field-Tested), B/O: $688.15

⎯

★ Flip Knife Doppler (Factory New), B/O: $547.93

★ Flip Knife Autotronic (Minimal Wear), B/O: $476.69

★ Flip Knife Case Hardened (Battle-Scarred), B/O: $278.18

★ Flip Knife Black Laminate (Well-Worn), B/O: $258.83

★ Flip Knife Urban Masked (Field-Tested), B/O: $181.64

⎯

★ Stiletto Knife Marble Fade (Factory New), B/O: $686.04

★ Stiletto Knife Doppler (Factory New), B/O: $665.41

★ Stiletto Knife, B/O: $601.39

★ Stiletto Knife Crimson Web (Field-Tested), B/O: $418.25

★ Stiletto Knife Night Stripe (Field-Tested), B/O: $227.80

★ Stiletto Knife Boreal Forest (Field-Tested), B/O: $194.96

★ Stiletto Knife Safari Mesh (Field-Tested), B/O: $192.79

⎯

★ Nomad Knife Crimson Web (Field-Tested), B/O: $518.11

★ Nomad Knife Scorched (Field-Tested), B/O: $169.78

★ Nomad Knife Forest DDPAT (Battle-Scarred), B/O: $166.88

★ StatTrak™ Nomad Knife Blue Steel (Field-Tested), B/O: $335.79

⎯

★ Skeleton Knife Stained (Well-Worn), B/O: $442.05

★ Skeleton Knife Urban Masked (Minimal Wear), B/O: $426.24

★ Skeleton Knife Boreal Forest (Field-Tested), B/O: $314.03

★ StatTrak™ Skeleton Knife Fade (Minimal Wear), B/O: $2361.28

★ StatTrak™ Skeleton Knife Urban Masked (Field-Tested), B/O: $376.53

⎯

★ Ursus Knife Doppler (Factory New), B/O: $557.12

★ Ursus Knife, B/O: $471.42

★ Ursus Knife Blue Steel (Minimal Wear), B/O: $212.37

★ Ursus Knife Case Hardened (Battle-Scarred), B/O: $187.66

★ Ursus Knife Damascus Steel (Field-Tested), B/O: $178.18

★ Ursus Knife Ultraviolet (Battle-Scarred), B/O: $155.13

★ Ursus Knife Boreal Forest (Battle-Scarred), B/O: $124.26

⎯

★ Huntsman Knife Black Laminate (Minimal Wear), B/O: $204.83

★ Huntsman Knife Black Laminate (Field-Tested), B/O: $184.50

★ StatTrak™ Huntsman Knife Lore (Battle-Scarred), B/O: $224.11

⎯

★ Bowie Knife Gamma Doppler (Factory New), B/O: $2142.02

★ Bowie Knife, B/O: $230.44

★ Bowie Knife Damascus Steel (Factory New), B/O: $209.20

★ Bowie Knife Ultraviolet (Minimal Wear), B/O: $180.51

★ Bowie Knife Ultraviolet (Field-Tested), B/O: $131.03

⎯

★ Falchion Knife Night (Field-Tested), B/O: $132.54

★ Falchion Knife Urban Masked (Well-Worn), B/O: $112.81

★ Falchion Knife Scorched (Field-Tested), B/O: $108.81

★ Falchion Knife Forest DDPAT (Field-Tested), B/O: $107.82

★ Falchion Knife Safari Mesh (Field-Tested), B/O: $107.46

★ StatTrak™ Falchion Knife Ultraviolet (Field-Tested), B/O: $143.08

⎯

★ Paracord Knife Crimson Web (Minimal Wear), B/O: $486.48

★ Paracord Knife Blue Steel (Battle-Scarred), B/O: $163.12

⎯

★ Survival Knife Blue Steel (Battle-Scarred), B/O: $138.26

★ Survival Knife Night Stripe (Field-Tested), B/O: $131.03

⎯

★ Gut Knife Sapphire (Minimal Wear), B/O: $1127.79

★ Gut Knife Gamma Doppler (Factory New), B/O: $286.17

★ Gut Knife Doppler (Factory New), B/O: $246.55

★ Gut Knife Marble Fade (Factory New), B/O: $240.77

★ Gut Knife, B/O: $210.49

★ Gut Knife Lore (Field-Tested), B/O: $194.22

★ Gut Knife Case Hardened (Battle-Scarred), B/O: $151.51

★ Gut Knife Blue Steel (Minimal Wear), B/O: $124.94

★ Gut Knife Rust Coat (Well-Worn), B/O: $118.99

★ Gut Knife Boreal Forest (Minimal Wear), B/O: $109.80

★ StatTrak™ Gut Knife Doppler (Factory New), B/O: $237.96

⎯

★ Shadow Daggers Gamma Doppler (Factory New), B/O: $264.92

★ Shadow Daggers Marble Fade (Factory New), B/O: $253.03

★ Shadow Daggers Tiger Tooth (Factory New), B/O: $237.22

★ Shadow Daggers Crimson Web (Field-Tested), B/O: $153.40

★ Shadow Daggers Autotronic (Minimal Wear), B/O: $144.42

★ Shadow Daggers Blue Steel (Field-Tested), B/O: $105.20

★ StatTrak™ Shadow Daggers Damascus Steel (Minimal Wear), B/O: $150.46

⎯

★ Navaja Knife Fade (Factory New), B/O: $365.99

★ Navaja Knife Doppler (Factory New), B/O: $228.93

★ Navaja Knife Marble Fade (Factory New), B/O: $227.43

★ Navaja Knife Slaughter (Factory New), B/O: $209.06

★ Navaja Knife, B/O: $203.16

★ Navaja Knife Case Hardened (Well-Worn), B/O: $132.57

★ Navaja Knife Damascus Steel (Factory New), B/O: $121.69

★ Navaja Knife Damascus Steel (Minimal Wear), B/O: $109.95

★ Navaja Knife Damascus Steel (Field-Tested), B/O: $100.41

★ StatTrak™ Navaja Knife Fade (Factory New), B/O: $369.01

★ StatTrak™ Navaja Knife Damascus Steel (Field-Tested), B/O: $109.95

GLOVES

★ Sport Gloves Amphibious (Minimal Wear), B/O: $2394.67

★ Sport Gloves Omega (Well-Worn), B/O: $572.33

★ Sport Gloves Bronze Morph (Minimal Wear), B/O: $338.88

★ Sport Gloves Big Game (Field-Tested), B/O: $323.66

⎯

★ Specialist Gloves Marble Fade (Minimal Wear), B/O: $1652.07

★ Specialist Gloves Tiger Strike (Field-Tested), B/O: $599.14

★ Specialist Gloves Crimson Web (Well-Worn), B/O: $231.57

★ Specialist Gloves Buckshot (Minimal Wear), B/O: $126.21

⎯

★ Moto Gloves POW! (Minimal Wear), B/O: $996.99

★ Moto Gloves POW! (Field-Tested), B/O: $383.31

★ Moto Gloves POW! (Well-Worn), B/O: $276.00

★ Moto Gloves Turtle (Field-Tested), B/O: $180.28

⎯

★ Hand Wraps CAUTION! (Minimal Wear), B/O: $502.29

★ Hand Wraps Giraffe (Minimal Wear), B/O: $180.73

★ Hand Wraps CAUTION! (Battle-Scarred), B/O: $178.32

⎯

★ Driver Gloves Queen Jaguar (Minimal Wear), B/O: $181.01

★ Driver Gloves Rezan the Red (Field-Tested), B/O: $101.66

⎯

★ Broken Fang Gloves Jade (Field-Tested), B/O: $127.88

★ Broken Fang Gloves Needle Point (Minimal Wear), B/O: $124.55

⎯

★ Bloodhound Gloves Guerrilla (Minimal Wear), B/O: $127.94

★ Hydra Gloves Case Hardened (Field-Tested), B/O: $102.55

WEAPONS

AK-47 X-Ray (Well-Worn), B/O: $478.95

AUG Hot Rod (Factory New), B/O: $425.83

StatTrak™ M4A1-S Hyper Beast (Factory New), B/O: $413.95

M4A4 Daybreak (Factory New), B/O: $309.51

StatTrak™ AK-47 Aquamarine Revenge (Factory New), B/O: $305.43

AK-47 Case Hardened (Well-Worn), B/O: $196.38

StatTrak™ M4A4 Temukau (Minimal Wear), B/O: $174.64

P90 Run and Hide (Field-Tested), B/O: $167.03

AWP Asiimov (Field-Tested), B/O: $153.33

Souvenir SSG 08 Death Strike (Minimal Wear), B/O: $140.00

M4A1-S Printstream (Battle-Scarred), B/O: $124.70

StatTrak™ M4A1-S Golden Coil (Field-Tested), B/O: $117.48

AWP Asiimov (Well-Worn), B/O: $115.97

StatTrak™ Desert Eagle Printstream (Minimal Wear), B/O: $112.96

StatTrak™ AK-47 Asiimov (Minimal Wear), B/O: $110.85

Souvenir M4A1-S Master Piece (Well-Worn), B/O: $102.42

AK-47 Bloodsport (Minimal Wear), B/O: $100.53

Trade Offer Link - Steam Profile Link - My Inventory

Knives - Bowie Knife, Butterfly Knife, Falchion Knife, Flip Knife, Gut Knife, Huntsman Knife, M9 Bayonet, Bayonet, Karambit, Shadow Daggers, Stiletto Knife, Ursus Knife, Navaja Knife, Talon Knife, Classic Knife, Paracord Knife, Survival Knife, Nomad Knife, Skeleton Knife, Patterns - Gamma Doppler, Doppler (Phase 1, Phase 2, Phase 3, Phase 4, Black Pearl, Sapphire, Ruby, Emerald), Crimson Web, Lore, Fade, Ultraviolet, Night, Marble Fade (Fire & Ice, Fake FI), Case Hardened (Blue Gem), Autotronic, Slaughter, Black Laminate, Tiger Tooth, Boreal Forest, Scorched, Blue Steel, Vanilla, Damascus Steel, Forest DDPAT, Urban Masked, Freehand, Stained, Bright Water, Safari Mesh, Rust Coat, Gloves - Bloodhound Gloves (Charred, Snakebite, Guerrilla, Bronzed), Driver Gloves (Snow Leopard, King Snake, Crimson Weave, Imperial Plaid, Black Tie, Lunar Weave, Diamondback, Rezan the Red, Overtake, Queen Jaguar, Convoy, Racing Green), Hand Wraps (Cobalt Skulls, CAUTION!, Overprint, Slaughter, Leather, Giraffe, Badlands, Spruce DDPAT, Arboreal, Constrictor, Desert Shamagh, Duct Tape), Moto Gloves (Spearmint, POW!, Cool Mint, Smoke Out, Finish Line, Polygon, Blood Pressure, Turtle, Boom!, Eclipse, 3rd Commando Company, Transport), Specialist Gloves (Crimson Kimono, Tiger Strike, Emerald Web, Field Agent, Marble Fade, Fade, Foundation, Lt. Commander, Crimson Web, Mogul, Forest DDPAT, Buckshot), Sport Gloves (Pandora's Box, Superconductor, Hedge Maze, Vice, Amphibious, Slingshot, Omega, Arid, Big Game, Nocts, Scarlet Shamagh, Bronze Morph), Hydra Gloves (Case Hardened, Emerald, Rattler, Mangrove), Broken Fang Gloves (Jade, Yellow-banded, Unhinged, Needle Point), Pistols - P2000 (Wicked Sick, Ocean Foam, Fire Element, Amber Fade, Corticera, Chainmail, Imperial Dragon, Obsidian, Scorpion, Handgun, Acid Etched), USP-S (Printstream, Kill Confirmed, Whiteout, Road Rash, Owergrowth, The Traitor, Neo-Noir, Dark Water, Orion, Blueprint, Stainless, Caiman, Serum, Monster Mashup, Royal Blue, Ancient Visions, Cortex, Orange Anolis, Ticket To Hell, Black Lotus, Cyrex, Check Engine, Guardian, Purple DDPAT, Torque, Blood Tiger, Flashback, Business Class, Pathfinder, Para Green), Lead Conduit, Glock-18 (Ramese's Reach, Umbral Rabbit, Fade, Candy Apple, Bullet Queen, Synth Leaf, Neo-Noir, Nuclear Garden, Dragon Tatto, Reactor, Pink DDPAT, Twilight Galaxy, Sand Dune, Groundwater, Blue Fissure, Snack Attack, Water Elemental, Brass, Wasteland Rebel, Vogue, Franklin, Royal Legion, Gamma Doppler, Weasel, Steel Disruption, Ironwork, Grinder, High Beam, Moonrise, Oxide Blaze, Bunsen Burner, Clear Polymer, Bunsen Burner, Night), P250 (Apep's Curse, Re.built, Nuclear Threat, Modern Hunter, Splash, Whiteout, Vino Primo, Mehndi, Asiimov, Visions, Undertow, Cartel, See Ya Later, Gunsmoke, Splash, Digital Architect, Muertos, Red Rock, Bengal Tiger, Crimson Kimono, Wingshot, Metallic DDPAT, Hive, Dark Filigree, Mint Kimono), Five-Seven (Neon Kimono, Berries And Cherries, Fall Hazard, Crimson Blossom, Hyper Beast, Nitro, Fairy Tale, Case Hardened, Copper Galaxy, Angry Mob, Monkey Business, Fowl Play, Anodized Gunmetal, Hot Shot, Retrobution, Boost Protocol), CZ75-Auto (Chalice, Crimson Web, Emerald Quartz, The Fuschia is Now, Nitro, Xiangliu, Yellow Jacket, Victoria, Poison Dart, Syndicate, Eco, Hexane, Pole, Tigris), Tec-9 (Mummy's Rot, Rebel, Terrace, Nuclear Threat, Hades, Rust Leaf, Decimator, Blast From, Orange Murano, Toxic, Fuel Injector, Remote Control, Bamboo Forest, Isaac, Avalanche, Brother, Re-Entry, Blue Titanium, Bamboozle), R8 Revolver (Banana Cannon, Fade, Blaze, Crimson Web, Liama Cannon, Crazy 8, Reboot, Canal Spray, Night, Amber Fade), Desert Eagle (Blaze, Hand Cannon, Fennec Fox, Sunset Storm, Emerald Jörmungandr, Pilot, Hypnotic, Golden Koi, Printstream, Cobalt Disruption, Code Red, Ocean Drive, Midnight Storm, Kumicho Dragon, Crimson Web, Heirloom, Night Heist, Mecha Industries, Night, Conspiracy, Trigger Discipline, Naga, Directive, Light Rail), Dual Berettas (Flora Carnivora, Duelist, Cobra Strike, Black Limba, Emerald, Hemoglobin, Twin Turbo, Marina, Melondrama, Pyre, Retribution, Briar, Dezastre, Royal Consorts, Urban Shock, Dualing Dragons, Panther, Balance), Rifles - Galil (Aqua Terrace, Winter Forest, Chatterbox, Sugar Rush, Pheonix Blacklight, CAUTION!, Orange DDPAT, Cerberus, Dusk Ruins, Eco, Chromatic Aberration, Stone Cold, Tuxedo, Sandstorm, Shattered, Urban Rubble, Rocket Pop, Kami, Crimson Tsunami, Connexion), SCAR-20 (Fragments, Brass, Cyrex, Palm, Splash Jam, Cardiac, Emerald, Crimson Web, Magna Carta, Stone Mosaico, Bloodsport, Enforcer), AWP (Black Nile, Duality, Gungnir, Dragon Lore, Prince, Medusa, Desert Hydra, Fade, Lightning Strike, Oni Taiji, Silk Tiger, Graphite, Chromatic Aberration, Asiimov, Snake Camo, Boom, Containment Breach, Wildfire, Redline, Electric Hive, Hyper Beast, Neo-Noir, Man-o'-war, Pink DDPAT, Corticera, Sun in Leo, Elite Build, Fever Dream, Atheris, Mortis, PAW, Exoskeleton, Worm God, POP AWP, Phobos, Acheron, Pit Viper, Capillary, Safari Mesh), AK-47 (Steel Delta, Head Shot, Wild Lotus, Gold Arabesque, X-Ray, Fire Serpent, Hydroponic, Panthera Onca, Case Hardened, Vulcan, Jet Set, Fuel Injector, Bloodsport, Nightwish, First Class, Neon Rider, Asiimov, Red Laminate, Aquamarine Revenge, The Empress, Wasteland Rebel, Jaguar, Black Laminate, Leet Museo, Neon Revolution, Redline, Frontside Misty, Predator, Legion of Anubis, Point Disarray, Orbit Mk01, Blue Laminate, Green Laminate, Emerald Pinstripe, Cartel, Phantom Disruptor, Jungle Spray, Safety Net, Rat Rod, Baroque Purple, Slate, Elite Build, Uncharted, Safari Mesh), FAMAS (Waters of Nephthys, Sundown, Prime Conspiracy, Afterimage, Commemoration, Dark Water, Spitfire, Pulse, Eye of Athena, Meltdown, Rapid Eye Move, Roll Cage, Styx, Mecha Industrie, Djinn, ZX Spectron, Valence, Neural Net, Night Borre, Hexne), M4A4 (Eye of Horus, Temukau, Howl, Poseidon, Asiimov, Daybreak, Hellfire, Zirka, Red DDPAT, Radiation Hazard, Modern Hunter, The Emperor, The Coalition, Bullet Rain, Cyber Security, X-Ray, Dark Blossom, Buzz Kill, In Living Color, Neo-Noir, Desolate Space, 龍王 (Dragon King), Royal Paladin, The Battlestar, Global Offensive, Tooth Fairy, Desert-Strike, Griffin, Evil Daimyo, Spider Lily, Converter), M4A1-S (Emphorosaur-S, Welcome to the Jungle, Imminent Danger, Knight, Hot Rod, Icarus Fell, Blue Phosphor, Printstream, Master Piece, Dark Water, Golden Coil, Bright Water, Player Two, Atomic Alloy, Guardian, Chantico's Fire, Hyper Beast, Mecha Industries, Cyrex, Control Panel, Moss Quartz, Nightmare, Decimator, Leaded Glass, Basilisk, Blood Tiger, Briefing, Night Terror, Nitro, VariCamo, Flashback), SG 553 (Cyberforce, Hazard Pay, Bulldozer, Integrale, Dragon Tech, Ultraviolet, Colony IV, Hypnotic, Cyrex, Candy Apple, Barricade, Pulse), SSG 08 (Death Strike, Sea Calico, Blood in the Water, Orange Filigree, Dragonfire, Big Iron, Bloodshot, Detour, Turbo Peek, Red Stone), AUG (Akihabara Accept, Flame Jörmungandr, Hot Rod, Midnight Lily, Sand Storm, Carved Jade, Wings, Anodized Navy, Death by Puppy, Torque, Bengal Tiger, Chameleon, Fleet Flock, Random Access, Momentum, Syd Mead, Stymphalian, Arctic Wolf, Aristocrat, Navy Murano), G3SG1 (Chronos, Violet Murano, Flux, Demeter, Orange Kimono, The Executioner, Green Apple, Arctic Polar Camo, Contractor), SMGs - P90 (ScaraB Rush, Neoqueen, Astral Jörmungandr, Run and Hide, Emerald Dragon, Cold Blooded, Death by Kitty, Baroque Red, Vent Rush, Blind Spot, Asiimov, Trigon, Sunset Lily, Death Grip, Leather, Nostalgia, Fallout Warning, Tiger Pit, Schermatic, Virus, Shapewood, Glacier Mesh, Shallow Grave, Chopper, Desert Warfare), MAC-10 (Sakkaku, Hot Snakes, Copper Borre, Red Filigree, Gold Brick, Graven, Case Hardened, Stalker, Amber Fade, Neon Rider, Tatter, Curse, Propaganda, Nuclear Garden, Disco Tech, Toybox, Heat, Indigo), UMP-45 (Wild Child, Fade, Blaze, Day Lily, Minotaur's Labyrinth, Crime Scene, Caramel, Bone Pile, Momentum, Primal Saber), MP7 (Teal Blossom, Fade, Nemesis, Whiteout, Asterion, Bloosport, Abyssal Apparition, Full Stop, Special Delivery, Neon Ply, Asterion, Ocean Foam, Powercore, Scorched, Impire), PP-Bizon (Modern Hunter, Rust Coat, Forest Leaves, Antique, High Roller, Blue Streak, Seabird, Judgement of Anubis, Bamboo Print, Embargo, Chemical Green, Coblat Halftone, Fuel Rod, Photic Zone, Irradiated Alert, Carbon Fiber), MP9 (Featherweight, Wild Lily, Pandora's Box, Stained Glass, Bulldozer, Dark Age, Hot Rod, Hypnotic, Hydra, Rose Iron, Music Box, Setting Sun, Food Chain, Airlock, Mount Fuji, Starlight Protector, Ruby Poison Dart, Deadly Poison), MP5-SD (Liquidation, Oxide Oasis, Phosphor, Nitro, Agent, Autumn Twilly), Shotguns, Machineguns - Sawed-Off (Kiss♥Love, First Class, Orange DDPAT, Rust Coat, The Kraken, Devourer, Mosaico, Wasteland Princess, Bamboo Shadow, Copper, Serenity, Limelight, Apocalypto), XM1014 (Frost Borre, Ancient Lore, Red Leather, Elegant Vines, Banana Leaf, Jungle, Urban Perforated, Grassland, Blaze Orange, Heaven Guard, VariCamo Blue, Entombed, XOXO, Seasons, Tranquility, Bone Machine, Incinegator, Teclu Burner, Black Tie, Zombie Offensive, Watchdog), Nova (Sobek's Bite, Baroque Orange, Hyper Beast, Green Apple, Antique, Modern Hunter, Walnut, Forest Leaves, Graphite, Blaze Orange, Rising Skull, Tempest, Bloomstick, Interlock, Quick Sand, Moon in Libra, Clean Polymer, Red Quartz, Toy Soldier), MAG-7 (Copper Coated, Insomnia, Cinqueda, Counter Terrace, Prism Terrace, Memento, Chainmail, Hazard, Justice, Bulldozer, Silver, Core Breach, Firestarter, Praetorian, Heat, Hard Water, Monster Call, BI83 Spectrum, SWAG-7), M249 (Humidor, Shipping Forecast, Blizzard Marbleized, Downtown, Jungle DDPAT, Nebula Crusader, Impact Drill, Emerald Poison Dart), Negev (Mjölnir, Anodized Navy, Palm, Power Loader, Bratatat, CaliCamo, Phoenix Stencil, Infrastructure, Boroque Sand), Wear - Factory New (FN), Minimal Wear (MW), Field-Tested (FT), Well-Worn (WW), Battle-Scarred (BS), Stickers Holo/Foil/Gold - Katowice 2014, Krakow 2017, Howling Dawn, Katowice 2015, Crown, London 2018, Cologne 2014, Boston 2018, Atlanta 2017, Cluj-Napoca 2015, DreamHack 2014, King on the Field, Harp of War, Winged Difuser, Cologne 2016, Cologne 2015, MLG Columbus 2016, Katowice 2019, Berlin 2019, RMR 2020, Stockholm 2021, Antwerp 2022, Paris 2023, Swag Foil, Flammable foil, Others - Souvenirs, Agents, Pins, Passes, Gifts, Music Kits, Cases, Keys, Capsules, Packages, Patches

Some items on the list may no longer be available or are still locked, visit My Inventory for more details.

Send a Trade Offer for fastest response. I consider all offers.

Add me for discuss if there is a serious offer that needs to be discussed.

CLICK FOR $5 SIGN UP BONUS
Attention, in order to withdraw the bonus, you need to deposit and use the investment offer at least once. Not depositing will result in an amount that won't be withdrawable. (Learned the hard way)
DAO Auto trading is a type of day trading that enables you to execute your trade on a daily basis Depending on the trade plan you subscribe into And subscription is free. DAO Auto trading is basically designed for new users in the crypto space or people with limited time. This helps you generates and compound profits on a daily basis without losses on your crypto investment and your auto trade plan runs for 5days. You get to earn on each days until your trade plan expires, then you can choose to activate a new trade plan or withdraw your trading profits and capital. All trades on auto trading are being executed by expertise that participate in ICO and IDO, which enables you earn passively through day trading of crypto currency.

CLICK FOR $5 SIGN UP BONUS
Attention, in order to withdraw the bonus, you need to deposit and use the investment offer at least once. Not depositing will result in an amount that won't be withdrawable. (Learned the hard way)
DAO Auto trading is a type of day trading that enables you to execute your trade on a daily basis Depending on the trade plan you subscribe into And subscription is free. DAO Auto trading is basically designed for new users in the crypto space or people with limited time. This helps you generates and compound profits on a daily basis without losses on your crypto investment and your auto trade plan runs for 5days. You get to earn on each days until your trade plan expires, then you can choose to activate a new trade plan or withdraw your trading profits and capital. All trades on auto trading are being executed by expertise that participate in ICO and IDO, which enables you earn passively through day trading of crypto currency.

CLICK FOR $5 SIGN UP BONUS
Attention, in order to withdraw the bonus, you need to deposit and use the investment offer at least once. Not depositing will result in an amount that won't be withdrawable. (Learned the hard way)
DAO Auto trading is a type of day trading that enables you to execute your trade on a daily basis Depending on the trade plan you subscribe into And subscription is free. DAO Auto trading is basically designed for new users in the crypto space or people with limited time. This helps you generates and compound profits on a daily basis without losses on your crypto investment and your auto trade plan runs for 5days. You get to earn on each days until your trade plan expires, then you can choose to activate a new trade plan or withdraw your trading profits and capital. All trades on auto trading are being executed by expertise that participate in ICO and IDO, which enables you earn passively through day trading of crypto currency.

CLICK FOR $5 SIGN UP BONUS
Attention, in order to withdraw the bonus, you need to deposit and use the investment offer at least once. Not depositing will result in an amount that won't be withdrawable. (Learned the hard way)
DAO Auto trading is a type of day trading that enables you to execute your trade on a daily basis Depending on the trade plan you subscribe into And subscription is free. DAO Auto trading is basically designed for new users in the crypto space or people with limited time. This helps you generates and compound profits on a daily basis without losses on your crypto investment and your auto trade plan runs for 5days. You get to earn on each days until your trade plan expires, then you can choose to activate a new trade plan or withdraw your trading profits and capital. All trades on auto trading are being executed by expertise that participate in ICO and IDO, which enables you earn passively through day trading of crypto currency.

Credit to u/SpacePaladin15 for the NOP Universe.
Hey, I hope everyone's doing well!
Today we return to the namesake of this fic, an actual lesson about animals. This one focuses on Koalas! One of Australia's most recognisable critters. I hope you enjoy.
It's hardly worth mentioning, seeing as I'm an infrequent poster at the best of times, but I'll not have another chapter out for a few weeks due to limited free time and devoting most of my writing time to an upcoming ficnapping. Be sure to look out for that!
[First] [Previous] [Next]
Memory transcription subject: Rysel, Venlil Environmental Researcher
Date [Standardised human time]: 8th September 2136
“Koalas!”
Bernard’s energised voice boomed through the air as the classroom's monitor flickered into life, images of this paws lecture topic popping up one after the other until the entire screen was filled with a collage of furry quadrupeds.
Squee! I’ll never get tired of this, it’s all so cool!
As usual the sight of something new stirred immediate discussion, hushed murmurs swelling into vibrant discourse in little more than a heartbeat. Most of the class swiftly huddled together into small herds to bounce ideas around while the rest opted to stick to the solace of their own thoughts as they took in the display.
I’d be quite happy in either situation, though seeing as Sandi had already sunk into deep concentration and Kailo had peeled off to talk with Ennerif and Solenk, it seemed the decision had been made for me on this occasion. Wasting no more time on idle inspection of the people around me, I focused my full attention forward, eager to form first impressions before the lesson began in earnest.
Now then, time to make some educated guesses. What traits does this animal have? I wonder if I’ll get any right this paw?
Professional assumptions went paw-in-paw with the lectures, examining and coming up with hypotheses about the specimens was only natural. Recently however, I’d started to make a little game of it to make things even more interesting than usual. A veritable bonfire of ideas had been set ablaze within me, fueled by my newfound knowledge of Earthen wildlife. Every flash and spark of the flame was a fresh theory I could try to apply to the lectures. It was an invigorating exercise that further stoked my unceasing wonderment.
So far I’d only done this once during the previous class and, to my disappointment, I’d not done too well.
I was right when I guessed that chickens were omnivores, but wrong in my assumption that they could fly. And that red thing on their head, the um… what was it called? The comb! Yes, the comb. I thought that was to attract mates, but it regulates body heat instead. It’s fascinating. Oh! Stars damn it I’m rambling!
I bapped my tail against my leg, the soft thud being just enough to snap me back from my runaway thoughts before I went completely wall-eyed. I was becoming more and more accustomed to getting lost in my own head while remaining conscious of the fact; it was happening so frequently now that it was pretty much impossible not to. Now I was able to pull myself back to the world around me without having to rely on someone else shaking me out of it. Most of the time anyway.
Sandi still keeps an eye on me, and Kailo even decided to help out once without being too snide about it. Anyway where was I? Oh yeah, Koalas.
Glancing at the furred animals, two things immediately stood out. Firstly, their eyes were in a more central position on their face. And second, all the images showed them being on or close to trees. There were other noteworthy observations of course, such as the Koala’s prominent nose and rounded features, but they fell to the wayside as I honed in on these points first.
Hmmm… ok. I already know to discount the idea that they’re predators just from eye position, so let’s get that thought out of here. Maybe omnivorous? Herbivore? Agh no, I can’t just guess that for the sake of guessing, that’s the same problem! Hrm, it’s tough making these assumptions now that everything I thought I knew has been turned on its head.
Nevermind, I’ll focus on the other thing. All the trees make me think they’re arboreal, that seems to be a reasonable assumption. I wonder what else they-
Clearing his throat, Bernard broke my concentration, his call for attention silencing the murmuring conversation and redirecting everyone's focus to the lecturer's podium.
His gaze panned across the room as he waited for everyone to settle, a beaming smile lighting up his face, “As ever I’m delighted to see you all get so into the subject matter from the get go. I’m looking forward to hearing what you were discussing should you wish to share. For now though, how about we get started, hm?”
A chorus of merry bleats rang out from across the audience, ears and tails flicking happily in agreement. Bernard's grin grew in tandem with the class's fervour, clasping his hands together enthusiastically as he launched into the lesson, “Excellent! Then let’s get started.”
The pictures on screen dissolved away until only one remained, enlarging to cover the entire monitor with the fluffy grey face of a Koala peacefully reclining in the crook of a tree.
“Ah, there we are,” Bernard’s baritone timbre drifted through the room as he looked up at the image, his own tone reflecting the relaxed attitude of the animal on screen, “He looks so comfortable doesn’t he? Perfectly at peace with the world, not too surprising considering they sleep almost 20 hours a day. A full paw!”
A wave of beeps and gasps rippled through the herd, punctuated by a single yawn-dressed comment from Rova, “A full paw? Hwuuu… jealous.”
Her drowsy remark elicited several whistling giggles from the herd, Bernard's own jovial chortle joining them as he turned to face her, “Late evening Rova?”
I twisted a little in my seat, panning an eye in Rova’s direction just in time to see her bleary eyes bulge open and her ears shoot up, now intensely aware of the fact she hadn’t been as quiet as she thought she had.
Sitting up abruptly, she hastily tapped down errant tufts of wool that’d flared in surprise as she composed herself, though her nervousness at becoming the centre of the class's attention was still plain for all to hear, “Uh- I um… achem, a little bit yes, um- …sorry. Lokki dragged me out to a movie viewing in the rec centre. It went on pretty late.”
A melodramatic bray from the other side of the room drew everyone's ears away from Rova to the now aghast Lokki, paw splayed across his chest in faux indignation, “Dragged you? Well excuse me for trying to broaden your horizons with human movies. That’ll be the list time I- …Ahaaaa…”
Lokki’s theatrics were cut short by a heavy yawn of his own, a swell of whistling laughter rolling through the herd as vibrant bloom lit up his snout, a sight that elicited a particularly amused bleat from Rova.
Turning away from the duo I looked back at Bernard, pleased to see that he was chuckling along with us. Behaviour like Lokki’s would never have been tolerated in my school and university days but, in stark contrast, Bernard revelled in it, the liveliness of his students fueling his own bombastic style of teaching. It was a pleasant change of pace having a teacher who let us all be ourselves in class; provided we weren’t too disruptive to the lesson plan.
Speaking of which.
His laughter still rumbling through the air, Bernard clapped his hands to pull everyone's focus back to him, “Ok, ok, let’s get back to it then shall we? Rova. Lokki. Hopefully the two of you can stay awake long enough until you can grab yourselves a coffee.”
As the class settled down and the last few giggling beeps petered out, Benard pointed a hand to the screen, “So, the Koala. Let’s start simple shall we? They are herbivorous marsupials native to the eastern and southern coasts of Australia. Easily recognised the world over, they are a well known and beloved symbol of their homeland, along with other animals such as the Kangaroo and the Emu. The former of which you might remember from one of our earlier lectures.”
Indeed I did remember, along with how angry Bernard had gotten after some speh-head had derided the Yotul after he explained how he held specific disdain for such attitudes.
Uuuggghh… I never want to see him angry again. So chilling.
I shook my ears in an effort to dismiss the unpleasant memory, panning my eyes back to the monitor to try and distract myself by inspecting the Koala’s physical appearance once more. Thankfully, by some Star's blessed intervention, Bernard had the exact same idea.
“Koala’s are rather squat in stature, ranging around sixty to eighty-five centimetres in length and weighing little more than fifteen to sixteen kilograms at their full size. As you can see, the fur of this fellow before you is a lovely silvery grey, but their fur can also sport a chocolaty brown hue as well. Arguably the most distinctive part of their appearance is their head, being rather large for their body size and having rounded ears, a large nose, and a pair of small eyes. These are often brown but variations do occur.”
It didn’t slip past my notice that Bernard didn’t bother to point out that the Koala’s eyes were forward facing. I didn’t think he’d simply forgotten, so perhaps he just felt it wasn’t necessary given that he’d already stated it was herbivorous. Either way, no one stuck up a paw or tail to question him.
“Now this will hardly be surprising considering how long they sleep, but Koala’s are largely sedentary and it’s rather easy to see why when you have a look into the contents of their diet.”
With the press of a button the Koala on screen was replaced by images of vibrant green vegetation. Soaring trees and flowering shrubbery weaved together across landscape framed pictures pulled admiring trills from the herd, the diversity of the plant life being shown standing as a reminder that it wasn’t only animal life that flourished on Earth.
After giving everyone the chance to take in the picturesque scenes, Bernard casually hammered that point home, “This is eucalyptus or, more accurately, a choice selection of more than 700 plants belonging to the eucalyptus genus, though the Koala itself favours 30 of them in particular.”
700!? Stars…
Realising that my ears had drooped in my momentary awe, I twisted them back to tune into the lesson, only for them to splay out in shock at the next words to come out of Bernard's mouth.
“The leaves of these plants are the primary food source of the Koala and there are a couple things worth mentioning when talking about these plants. For starters they do not have much nutritional or caloric value, leading to the Koala’s low-energy lifestyle. Additionally, they contain toxic compounds.”
A shiver instantly ran through the herd, ears flicking rapidly in confusion and alarm followed by a few quizzical whispers. It didn’t take long for someone to decide to give a proper voice to the murmuring.
“Excuse me Doctor. Did we hear that right? Their diet is made up of toxic flora?” Vlek’s grumbling incredulity cut through the herd's mutterings with ease. Until Kailo’s recent change of heart, the fifty something rotation old blonde Venlil had been a close second in terms of scepticism. Mercifully his rebuttals had always been relevant questions as opposed to ranting diatribes, so he at least remained on topic if nothing else.
Bernard nodded in confirmation, smiling back at Vlek while absentmindedly twirling the end of his moustache, “You heard me right, they do indeed consume plants that are toxic. Just not to them.”
Any worry or uncertainty still clinging to the herd was swept away by the provision of the glaringly obvious answer, leaving me chuckling inwardly at the oversight.
Ah of course! The plant might be poisonous but they’ll have evolved to deal with that. Stars… I’m so used to expecting the unexpected with Earth that I didn’t even consider the simplest solution.
“I see, thank you Doctor,” Vlek replied, a tinge of interest still audible in his tone, “I assume they’ve developed some adaptation to become immune to the harmful effects?”
The question immediately evoked a smirk from our teacher, but he hurriedly suppressed it while bobbing his head, “They have indeed. There are several factors that aid in their digestion of eucalyptus leaves without succumbing to the plant's baleful properties. The first is a part of the intestinal tract called the cecum. It contains a microbiome that allows the Koala to digest the eucalyptus. Coupled with this is an enzyme in the Koala’s liver that helps them break down the toxins. They are also capable of sniffing out the plants with the least amount of toxins, ensuring that they ingest as little as possible.”
Pausing for a breath Bernard looked back at the screen before turning to face us, another grin curling at the edges of his mouth as he continued with his explanation, “This is mostly for adult Koala’s, because while their young also possess these same adaptations, they don’t just go straight to munching through foliage right after being born. No, they need a little help making that jump and getting a stomach full of all that good gut bacteria. It’s nothing bad, but those of a sensitive stomach may wish to prepare themselves for this next part.”
Bernard’s assurances did little to assuage the concern that his warning had foisted upon us. Having been exposed to so much of the weirdness Earth had to offer everyone always ended up on edge whenever Bernard gave advice like this, even if he did say it in jest.
What strange nonsense thing do Koala pups do then? Judging by the way he’s acting it probably isn’t something as simple as drinking milk from the mother. Hmmm…
“So,” Bernard began, snapping us from our pensive stupor, “Young Koala’s, known as joeys, have a gestation period of thirty-five days on average, which is approximately forty-two paws. Once born they travel from the birth canal to a pouch in their mother so that they can continue to develop and grow. In the pouch the joey finds and latches onto one of two teats and these provide the newborn with a steady stream of nourishing milk. It spends the next six to seven months growing in the pouch, its eyes, ears, and fur all developing as time goes on.”
Okay, interesting. But this is exactly how I thought it’d go. What’s different?
The unexpected normalcy of the Koala’s birth and growth cycle had calmed everyone's nerves, only to be replaced with an air of suspicion as we waited with rapt attention for Bernard to drop the other claw and upend our expectations like he always did.
Not wanting to keep us in further suspense he forged ahead, the tempo of his voice picking up as the smile started to crease his face once more, “Now to make the switch from milk to eucalyptus, the mother also feeds the joey a substance called pap. It comes from the cecum I mentioned earlier, and contains all the gut bacteria required to help the young Koala in making the switch to eucalyptus.”
He stopped and looked around, searching us for a reaction to what I felt was a rather bland statement of fact. What was it he was saying without actually saying? Koala pups drink milk to mature and then include this pap substance so that they can start eating plants. I don’t see what-
The cecum is part of the intestine.
I blinked.
I blinked again, the intrusive interruption scouring my brain clean of any other thought bar the one it’d just implanted itself in the forefront of my mind.
Oh stars. They-
“They eat their own poop!?”
The shocked bleat shattered the peace of the room to reveal that most if not all of us had come to the same tail curling conclusion. As the hall filled with unrestrained vocalisations of disgust, an ‘Ugh’ over here and a ‘Blegh’ over there, Bernard’s own bellowing laughter joined the throng of voices.
“Ha! Everytime! Each and every time. Clearly it doesn’t matter if my students are Human or Venlil. Whenever someone learns about the Koala’s dietary development the reaction is the same!”
Pleased with himself beyond reason, Bernard chuckled away while the rest of us grappled with this ghastly reality. While there were plenty of animals that feasted on things that ranged from simply unappealing all the way to the stomach churningly grotesque, I’d never heard of an animal that actively consumed the excrement of its own species. Benefits aside, the prospect of having to do that to survive to adulthood sent a shiver of revulsion down my spine.
Ewww… Stars, I hope I forget this feeling by 2nd meal. They’re serving sturen and magamroot stew later. I was really looking forward to it.
With the herds mood beginning to temper Bernard tapped the podiums controls, removing the verdant collage of eucalyptus to display several similar yet distinct environments, still chortling merrily to himself in the process, “Ok then, with that little foray into their diet complete, why don’t we look at their habitat in more detail? As you might imagine given their diet and arboreal nature, Koala’s live in forested regions, and can be found in tropical and temperate zones. About a century ago they were classed as a vulnerable species, however efforts were made to turn this around and increase their numbers. Sadly the largest factor in their decline was human activity, as the fertile lands that gave rise to their bountiful forests were coveted farm land for our settlements.”
It was strange to hear Bernard so matter of factly admit to humanity's negative impacts on other species. He’d alluded to such things in the past but always with an air of caution, carefully pawing the line between honestly answering a question while not painting humanity as uncaring and destructive. AKA, the ‘predators’ we’d all initially expected them to be.
Perhaps his comfort in making such admissions was a reflection of the class's comfort with him, for no one so much as batted an ear. Even Kailo, who I would’ve expected to jump at the chance to use this as a prime example of predatory danger, only flicked an ear in stern yet silent concern.
A cough from Bernard drew my attention back, a new picture on screen that showed a forest from a bird's-eye view. Drawn across the image were around a dozen ringed areas, some bordering one another while others overlapped to some degree. It took me a moment, but I soon recognised that what I was looking at was a map, the rings representing what I assumed to be territories. And it didn’t take much effort to guess who each one belonged to.
“From habitats we move onto behaviours, so let’s start with territories. Koala’s are solitary animals. Yes, despite being herbivores. Considering they’re only awake for roughly four hours of the day I can hardly blame them. Lots to do and not a lot of time to do it. Jokes aside, once they mature they are quite independent, carving out a little slice of land for themselves, as displayed in this example, called a Home Range. That is not to say they go it alone and leave everything else behind however. Rather, as shown in the map behind me, they live in their own space while still being part of a larger social group.”
With another press of his pad the picture was updated to show one of two symbols in each segment, along with a key to the side of the map displayed in helpful Venlang. A quick glance told me that the symbols were representing whether the territory belonged to a male or female of the species.
“As you can see there is quite a bit of overlap between different Koala’s territories. It is in these areas that most of the socialising takes place between neighbours. The trees in these locations represent the few areas where intrusion across territories is acceptable for the sake of social interaction. Outside of that the Koala’s stick to their own territories for the most part, with the exceptions of Koala’s who are passing through, attempting to become part of the social group themselves, or dominant males who sometimes go off into another Koala’s range. But how do they know where one range begins and another range ends you might ask? Well, this brings us onto the next part of the lecture. How do Koala’s communicate?”
Wiping away the map from the monitor, Bernard loaded up a video of a Koala sitting in a tree and pressed play. Head held high, the Koala’s body shook as it belted out a reverberating call into the wilderness that could only be described as a garbled combination of a car engine failing to turn over mixed with the hiccups of someone with a particularly sore throat.
That’s how they sound? Oof that must be rough on the lungs.
I clearly wasn’t the only one to share such a thought, because I clocked Sandi tracing a paw along her neck as the noise went on, ears fluttering in discomfort at the noise.
Bernard himself cleared his own throat as the video came to an end, minimising it and replacing it with another image of a tree with a Koala rubbing up against the bark, “I think they’ve got me beat on who’s got the deeper voice!”
His joke garnered several amused beeps, a rare reaction that caused a beaming smile to shine across his face at lighting speed, “Oh you’re too kind. I’ll be here all week. Now where were we? Oh yes! Communication. As you’ve just heard, Koala’s are capable of loud low pitched bellows that can carry over vast distances. These express everything from ‘Hello I’m over here’ to ‘This is my turf, stay away’. Bellowing is more common in the males than the females, opting for shouting matches as opposed to outright fights when it comes to asserting dominance. Other vocal expressions include grunts, wails, and snarls if they’re acting particularly angsty. Mother and joey pairs also communicate through gentle clicking, squeaking, and murmuring sounds. And there’s one more thing worth mentioning. Something they have in common with Humans and Venlil when it comes to emoting.”
Really? They do something we do?
Curious, I pressed myself against the desk, straining as close as I could to once more scrutinise the Koala’s features. Not a lot stood out to me at first, the grey marsupial not sharing many similarities with a Venlil that I could identify.
Ok think. We show emotion with our ears, tails, and our wool on occasion. They don’t have tails so it’s obviously not that. Wool standing on end is more a reaction than a conscious expression. So it must be the ears then.
To my quiet satisfaction, my hunch was soon validated by Bernard, “As well as their vocalisations, Koala’s are very emotive through their facial features. Just like humans, they use their mouths and lips to show how they feel, but these tend more towards the aggressive side of the scale than what you might see on a human. Regarding yourselves however, Koala’s utilise their ears in tandem with their mouth movements when showing strong emotion.”
I was delighted to hear that my assumption was correct, a little happy flick twisting out through my tail and bapping against my chair with a muted thump against the plastic.
Hehe yes! Got one right!
“Now then, we are getting close to lunchtime so I’ll finish this segment off with something I think you’ll find particularly interesting. Diplomacy.”
Perplexed mutterings followed in the wake of the bizarre inclusion to the lecture, my own thoughts being dominated by bewilderment as I tried and failed to make sense of how the two could possibly be related.
Why would Koala’s, or any animal for that matter, be linked to diplomacy? Hmmm...
I could understand dispatching exterminators to deal with a predator issue as a show of goodwill, that at least includes animals, but Humans aren’t like that so I think I can safely scratch that off the list.
Maybe the humans who live in that region benefited from Koala’s in some way. Could they have gotten something from them? But what?
Hopefully not what the pups get from their mothers.
Agh no! Begone awful intrusive thoughts. Blegh! I don’t need that in my head.
As I wrestled with the short-lived revulsion inflicted upon me by my Star's damned subconscious, Bernard placed a new image on screen, one that was decidedly different from all that had preceded it.
On screen were more than a couple dozen pictures of humans. Some were pictured alone while others congregated in large groups while cameras surrounded them from all angles. Across all the images, I noted two common themes. First of all, a solid majority of the humans were wearing formal wear similar to what I’d seen worn by UN representatives on TV. If the gaggle of journalists in the background of the photos didn’t already confirm my suspicions, then it was this similarity which made me conclude they were all people of some importance. Likely politicians judging from context clues.
Secondly, each of the individuals was interacting with a Koala in some form. Some cradled one against their chests while others were feeding it eucalyptus leaves or pellets of some kind. One of the assumed politicians had become an impromptu bed for a snoozing bundle of fur, a gleeful smile spread across their face as they lovingly gazed down at the sleeping Koala in their lap.
As I continued to stare at the assorted photos something clicked into place, a sudden spark flickering into life. A burgeoning light of comprehension that flared and swelled with every wide-eyed breath I took. Some things still escaped me, things I hoped would soon be explained, but in staring at all of the humans happy smiling faces, I was struck with an instant of pure understanding.
If someone, say a Nevok for instance, offered to gift me a creature that was common to them but which might exotic and breathtaking to a Venlil, how could my feelings not be swayed? How could I walk away from that encounter and not have grown closer to them as a result?
“Koala diplomacy,” Bernard waved his hand up at the monitor, a slight reverence in his tone, “My favourite kind of soft power diplomacy. Where political leaders take photo ops with Koala’s and, on occasion, the Australian government loans Koala’s to other nations for a time to bolster positive relations. It certainly helps that Koala’s are a beloved animal worldwide, drawing large crowds and revenue for countries fortunate enough to host the adorable critters.”
The truly alien concept predictably sparked instant discussion in the herd, two polar opposite schools of thought swiftly cementing themselves as the most popular opinions. Simultaneously, I heard one voice trill excitedly while another scoffed at what they clearly saw as a ridiculous and offensive notion.
“Squee! That’d be so cool! I’d love to get the chance to see a Liri from Coila. Remember the Rainbow Boa? Think of that shimmering effect and colour but put it on a bird! Ah! I’ve only heard their song on video. It’d be a treat to hear it in person!”
Ooo! I’ve read about them! I’d love to get up close to one.
“Loaning. As if animals are property to be hoarded and traded? Pugh! Another predatory trait the humans don’t want to acknowledge for what it is.”
Ugh, typical. Jump right to the worst possible option.
However, despite my dismissal of their disparaging fumings, an uncomfortable thought pressed upon my mind. While it was plain to see how much humans cared for the Koala, it didn’t change the fact that humans did keep animals as property just as the scornful herd member had said.
This begged a rather important, disquieting question. Aside from keeping some animals as cattle, a stomach tightening minefield I had no desire to step a claw onto right now, how else did humans keep other creatures. And how did they treat them?
Before I was fully conscious of doing it my paw was in the air, the question primed on my tongue.
Noticing my elevated paw Bernard pointed at me, smiling warmly, “Yes Rysel? What’s on your mind?”
Sorry Bernard. I hope this one’s not too awkward for you to answer.
Flicking my ear in appreciation, and waiting for everyone to settle enough so that I could be heard, I voiced my concerns as neutrally as possible, “Thank you Doctor. I uh, just had a thought. We know that humans keep certain animals for… particular reasons, and we know why. From how you’ve spoken about Koala’s I think it's fair to say that the same cannot be said for them. However, this makes me wonder, what other reasons do humans have for keeping animals and how do you treat them?”
A flash of surprise blinked across Bernard's eyes but vanished so quickly that it felt like I’d imagined it. Had he not expected such a question? Maybe he was just shocked that it’d been me who’d ended up asking it?
Stars, am I so predictable that no one expects me to ask difficult questions?
Unfortunately, a quick glance at my deskmates seemed to prove that to be the case, as both Sandi and Kailo were looking at me with differing degrees of astonishment flapping in their ears.
Well speh.
“A very good point Rysel, certainly one that’s worth raising. Yet another example of you all anticipating what I have to say before I can bring it up myself.” Bernard tapped the podium, switching off the monitor before returning his focus to me, “We won’t be needing that. I’ve nothing prepared that I can show you and we’re heading to lunch in a few minutes anyway. Still, that’s plenty of time to give you a bit of an answer.”
A bit? What does he mean just a bit?
Made even more curious by Bernard's preempted admission that he wasn’t going to fully answer my query, I dialled both my ears on him, fixing him with an inquisitive stare as he started to explain with a tone that was noticeably more nonchalant than any of his previous explanations.
“So, animals in captivity for reasons other than what you already know. Honestly I would love to delve into other reasons regarding why we keep animals. However, I have a lesson plan in the works that I hope to share with you all in the not too distant future. Some of it touches upon this very topic and I’d quite like to bundle it all together. That said, I can tell you how animals in captivity are treated. In short, the answer is very well. There are a mountain of laws both on private and public interests that govern the standards and ethical treatment of animals, and breaches of these laws are quite severe even for relatively minor infractions.”
While I’d be lying if I said I wasn’t disappointed by the vague answer to what was really the bulk of my question, I was at least satisfied by Bernard’s assurances that animals in captivity, such as the Koala, were well looked after. Considering the barely subdued grumbling coming from some corners of the audience it was clear that several of the herd didn’t believe Bernard outright, but I trusted him to be honest. Additionally, the mention of an upcoming lecture focused on humans keeping animals caused quite the buzz.
I felt a mix of excitement and trepidation at exploring the topic further. He’d pretty much confirmed we wouldn’t be talking about cattle farms, for which I was relieved, but that still left a huge amount of uncertainty in what was to come.
Humans keeping animals as cattle was a forgone conclusion. As horrifying as that reality was, it was one I could understand from a detached and strictly clinical point of view. Being predators they ate meat and therefore they kept cattle. But the concept of keeping animals for any other reason baffled me.
What could be the purpose? The diplomacy thing makes sense now that I have context, but what other reasons could they have.
The class's discussions were interrupted by the recognisable ring of the break bell, the shift in attention eliciting a change in conversation from confused hypotheses to peppy conversation on how everyone was planning to spend their break and what they had in mind for 2nd meal.
“Well I can see everyone’s excited for lunch, and who am I to disappoint,” chuckling Bernard waved us all up from our seats, pocketing his pad from the podium and heading to open the classroom door for us, “Enjoy your break, get a good rest along with a hearty meal, and I’ll see you all back here at the usual time.”
As everyone else filed out I stayed behind, waving at Sandi and Kailo as they left, and pawing over to Bernard once he and I were the only ones left in the room.
Ears folded down and with an apologetic tinge in my voice I greeted him as I sidled up to him, “Hey Bernard, I uh… sorry if that last question was unexpected.”
Chortling in reply, Bernard waved a hand through the air in a sign I’d come to understand meant ‘not a problem’.
“No need to apologise Rysel. It was a good question and most certainly not a problem.”
Heh, called it.
I sighed, allowing tension I didn’t realise I’d been holding to relax itself from my shoulders, “Phew, that’s a relief. I’m glad. I’m curious to hear what this new lesson is you’ve got in store for us by the way.”
Bernard wagged a finger at me, throwing up his eyebrows in mock amazement, “Oh are you now? Well I’m afraid you’ll have to remain curious for the time being. It’s going to be quite the surprise if all goes to plan. But…”
He trailed off, glancing at me before looking to the door like he was making sure no one else was around.
Wait, is he going to tell me? Oh please yes let me know now!
Stopping myself from jumping on the spot in excited anticipation, and trying my damndest to stop my tail from wagging in equal measure, I stared up at Bernard as he stewed in his thoughts before turning back to face me.
“I can’t tell you the specifics, but I’m working with Alejandro and Tolim to get something together. A trip that’s not a trip as it were. And when it happens, I’m going to need a few of the more accepting members of the class to lend me a hand. I’m hoping you and a couple others will be able to help with that?”
A trip that’s not a trip? What does that mean? Agh who cares about that right now! Bernard’s relying on me to help out!
Still trying not to keep myself from bouncing around with pup like glee I swished my tail and nodded my head in joint agreement, happy to help with whatever Bernard had in store for us, “Of course! Anything you need I’ll be there to lend a paw. You can count on me!”
A broad warm smile lit up Bernard's face, a hand patting me on the shoulder in appreciation, “Thank you Rysel. I knew I could rely on you but it still warms my heart to hear it. And, as thanks for this and for the many times you’ve shown your support, the surprise includes a little something special I think you’d appreciate the most.”
If my earlier enthusiasm had been at a nine, then the implication of a supposed gift sent it rocketing all the way to a hundred in a heartbeat.
“Wait… WHAT!? What do you mean? What are you doing?”
As impossible as it seemed, Bernard's grin grew even wider as I almost lost myself in wool shaking exhilaration, “Call it my own form of Koala diplomacy. But I’m afraid that’s all I can say for now. Wouldn’t want to ruin the surprise even for you!”
“Oh you ass!” Whistling jovially I bapped my tail against Bernard’s leg in fake indignation, evoking a barking bellowing laugh from the man himself.
Still laughing, the two of us departed the class and made for the canteen, my rumbling stomach leading me on while my mind spun with fantastical thoughts as to what Bernard had prepared for us.
And what specifically he had in store for me.

With the release of beast-yeast episode 3, we're going to be removing weekend level help threads for episodes 1 and 2. I've edited the rules to state this

This is the [regularly-scheduled] megathread! Stuff that isn't cool enough to have its own post can go here.

What toppings should you put on [character]? Does [character] fit in this PvP team? Feel free to talk about it here! We only ask that before you ask, you check the

Community Resources (Please read these before asking a question! Your question may be answered here!)

Cookie Run Kingdom Resource
The Complete Full AUTO Master Mode Guide by dlmenslon
Sublime Cake Tower walkthrough

Frequently Asked Questions

• Newbie FAQ by DrRoboMagi
• How to Build a Team in Cookie Run Kingdom
• FAQ: Treasures: You're probably using them wrong
• FAQ: Help, I'm stuck on [level]!
• FAQ: Shop - What should I spend my IRL money on?
• FAQ: Crystals. What should I spend my crystals on? Which landmark do I get?
• FAQ: Power, Stats, Topping, that kind of thing
• FAQ: Whats with Devsisters and NFTs?

Search for Friends / Guilds (by server)

(I think this only works on browser):

• Vanilla
• Hollyberry
• Cacao

Hi everyone. This is my first Reddit post, so please pardon if I am using some wrong format.
I want to learn about Fine Tuning LLMs such as LLama-2, Gemma models, Llama-3. I have read plenty of medium articles and have been exposed to plenty of new topics such as LoRA, QLoRA, PEFT, etc. I have tried my best to understand them. But while implementing the code by following along the medium articles, I sometimes come across numerous parameters that are initialized without explanation which is overwhelming sometimes. I have also been exposed to Unsloth. I want to know where can I begin from. Should I begin with understanding how to fine-tune small models such as BERT, T5, etc using PyTorch and Transformers library? If you would like to provide some roadmap it would be really helpful. Thank you for your time.
I am attaching an example of the code I struggled to understand. How does one know which parameters are supposed to be used and which not?

model_name = "NousResearch/Llama-2-7b-chat-hf" dataset_name = "mlabonne/guanaco-llama2-1k" new_model = "Llama-2-7b-chat-finetune" # QLoRA parameters lora_r = 64 lora_alpha = 16 lora_dropout = 0.1 #bitsandbytes parameters #activate 4-bit precision base model loading use_4bit = True #compute dtype for 4-bit base models bnb_4bit_compute_dtype = "float16" #quantization type fp4 or nf4 bnb_4bit_quant_type = "nf4" #activate nested quantization for 4 bit base models use_nested_quant = False #training parameters #output dir output_dir = "./results" #no. of training epochs num_train_epochs = 1 fp16 = False bf16 = False per_device_train_batch_size = 4 per_device_eval_batch_size = 4 gradient_accumulation_steps = 1 gradient_checkpointing = True max_grad_norm = 0.3 learning_rate = 2e-4 weight_decay = 0.001 optim = "paged_adamw_32bit" lr_scheduler_type = "cosine" max_steps = -1 warmup_ratio = 0.03 group_by_length = True save_steps = 0 logging_steps = 25 # SFT Parameters # Maximum sequence length to use max_seq_length = None # Pack multiple short examples in the same input sequence to increase efficiency packing = False # Load the entire model on the GPU 0 device_map = {"": 0} # Load dataset (you can process it here) dataset = load_dataset(dataset_name, split="train") # Load tokenizer and model with QLoRA configuration compute_dtype = getattr(torch, bnb_4bit_compute_dtype) bnb_config = BitsAndBytesConfig( load_in_4bit=use_4bit, bnb_4bit_quant_type=bnb_4bit_quant_type, bnb_4bit_compute_dtype=compute_dtype, bnb_4bit_use_double_quant=use_nested_quant, ) # Check GPU compatibility with bfloat16 if compute_dtype == torch.float16 and use_4bit: major, _ = torch.cuda.get_device_capability() if major >= 8: print("=" * 80) print("Your GPU supports bfloat16: accelerate training with bf16=True") print("=" * 80) # Load base model model = AutoModelForCausalLM.from_pretrained( model_name, quantization_config=bnb_config, device_map=device_map ) model.config.use_cache = False model.config.pretraining_tp = 1 # Load LLaMA tokenizer tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True) tokenizer.pad_token = tokenizer.eos_token tokenizer.padding_side = "right" # Fix weird overflow issue with fp16 training # Load LoRA configuration peft_config = LoraConfig( lora_alpha=lora_alpha, lora_dropout=lora_dropout, r=lora_r, bias="none", task_type="CAUSAL_LM", ) # Set training parameters training_arguments = TrainingArguments( output_dir=output_dir, num_train_epochs=num_train_epochs, per_device_train_batch_size=per_device_train_batch_size, gradient_accumulation_steps=gradient_accumulation_steps, optim=optim, save_steps=save_steps, logging_steps=logging_steps, learning_rate=learning_rate, weight_decay=weight_decay, fp16=fp16, bf16=bf16, max_grad_norm=max_grad_norm, max_steps=max_steps, warmup_ratio=warmup_ratio, group_by_length=group_by_length, lr_scheduler_type=lr_scheduler_type, report_to="tensorboard" ) # Set supervised fine-tuning parameters trainer = SFTTrainer( model=model, train_dataset=dataset, peft_config=peft_config, dataset_text_field="text", max_seq_length=max_seq_length, tokenizer=tokenizer, args=training_arguments, packing=packing, ) # Train model trainer.train() 

Kingdom of the Planet of the Apes was one of the biggest blockbuster movies of last summer. The latest installment in the rebooted Planet of the Apes franchise, it continues the story of Caesar's ape rebellion against their human oppressors. With stunning visual effects and a thought-provoking storyline, it's no wonder the film was a huge hit.

🟩CLICK HERE TO WATCH ONLINE

If you missed catching Kingdom of the Planet of the Apes in theaters, you may be wondering how and where you can watch it online now. The good news is there are a few legitimate options to stream the movie, including some ways to watch it for free. Here's a rundown of how you can watch Kingdom of the Planet of the Apes online:
Watch It With Your Cable/Streaming Subscription For those who have a cable subscription or streaming services like Hulu + Live TV, FX+, YouTube TV or DirecTV Stream, you can watch Kingdom of the Planet of the Apes through those providers. The movie is available on-demand through premium channels like HBO, Cinemax, Starz and Showtime if you have subscriptions to those as well.
Free Streaming Option Your best option for watching Kingdom of the Planet of the Apes online for free is by signing up for a free trial to a streaming service that has the movie available. Hulu + Live TV, DirecTV Stream and FuboTV all currently have the film in their libraries and offer free week-long trials for new users.

🟩CLICK HERE TO WATCH ONLINE

Just sign up, watch the movie during your free trial period, and cancel the subscription before you're charged if you don't want to keep the service. Just don't forget to set a reminder to cancel before the trial ends!
Rent or Buy Online If you'd prefer to just rent or purchase Kingdom of the Planet of the Apes outright, it's available through all the major digital retailers. You can rent the movie for about $5.99 or buy it for around $19.99 from Amazon Prime Video, iTunes, Vudu, Google Play, YouTube and others.
While renting is cheaper, buying it lets you watch the movie as many times as you'd like and is a good option for fans who know they'll want to revisit this latest Apes film again.
So those are the primary ways to watch Kingdom of the Planet of the Apes online right now. Whether you want to stream it for free, rent it temporarily, or buy it to own, there are plenty of easy options to watch one of last year's biggest hits from the comfort of your home. Just be prepared for some jaw-dropping visual effects and a healthy dose of philosophizing on the nature of humanity, animality and freedom.

🟩CLICK HERE TO WATCH ONLINE

Where to Watch Furiosa: A Mad Max Saga Online for Free
The highly anticipated new installment in the Mad Max franchise, Furiosa: A Mad Max Saga, hit theaters last weekend amid tons of buzz and hype. The post-apocalyptic action film serves as both a prequel to 2015's Mad Max: Fury Road and the beginning of a new trilogy set in that harsh, desert wasteland world.

🟥CLICK HERE TO WATCH ONLINE

Starring Anya Taylor-Joy in the title role originated by Charlize Theron, along with Chris Hemsworth and Tom Hardy reprising his Fury Road character, Furiosa has been praised by critics as a visual spectacle and thrilling ride. If you missed catching it on the big screen this opening weekend, you may be wondering where to watch Furiosa online and how to stream the new Mad Max movie from home.
Unfortunately, as a brand new theatrical release, there is no legitimate way to stream Furiosa for free online yet. The only way to watch it right now is to buy tickets at your local movie theater. It will likely be several months before Furiosa becomes available to rent or purchase on digital platforms like Amazon Prime, iTunes, Vudu, etc.
However, there are always shady websites claiming to allow you to watch Furiosa online or stream the full movie for free. These sites are extremely unreliable and often spread malware or viruses. Most don't actually have the movies they claim to offer. Typing phrases like "watch Furiosa online free" into search engines is a surefire way to encounter these scam sites.

🟥CLICK HERE TO WATCH ONLINE

When and Where Can I Stream Furiosa at Home?
So when and where will Furiosa actually become available to stream online? The typical theatrical window for new releases is around 90 days (about 3 months) before movies become available for digital rental/purchase. So if Furiosa follows a similar timeline, you could expect to see it on-demand sometime in early September 2024.
After that, it will likely become available for streaming subscription on services like HBO Max, Hulu, or Netflix around 5-7 months after its theatrical premiere. So subscribing to one of those platforms by October or November will allow you to stream Furiosa from home with no extra rental fee.
Of course, Warner Bros could always change up the release strategy. But in general, your best way to watch new movies online is waiting patiently and avoiding those sketchy "free streaming" websites that promise the impossible. Trust me, it's worth the wait to watch Furiosa: A Mad Max Saga at home the legitimate way later this year. The explosive action and stunning visuals deserve to be seen properly.

🟥CLICK HERE TO WATCH ONLINE

The CEO and Founder of Sweet Loren's, Loren Castle, is on a mission to enhance the lives of as many people as possible with her delicious "better-for-you" baked goods. As the #1 natural cookie dough brand in the US, Sweet Loren's is taking indulgence to a whole new level.
Having endured a life-altering battle with cancer at just 22, Loren pleaded with the universe that if she not only survived, but thrived after, she would turn her struggle into her greatest strength. Loren realized that the only way she could beat cancer was by staying positive, so she devoted all of her energy to becoming healthy and baking delicious treats. Sweet Loren’s was born from Loren's passion to create a gluten-free, vegan cookie that was equally delicious. Loren quickly realized that this was no longer about her, but creating a brand that would impact millions of people’s lives for the better. Deeply fueled by her mission, Loren makes sure to live her life with no regrets and only expect greatness.
Tune In! https://podcasts.apple.com/us/podcast/sweet-resilience-from-cancer-survivor-to-natural-cookie/id1426026971?i=1000656247322

Choosing a data source Before diving into AI and big data, choose a reliable and free data source to get historical stock market data. One popular option is Alpha Vantage (https://www.alphavantage.co/). Sign up for a free API key and access a wealth of stock data.
Example: Fetching stock data from Alpha Vantage in Python:
​

import requests api_key = 'your_alpha_vantage_api_key' symbol = 'MSFT' function = 'TIME_SERIES_DAILY' url = f'https://www.alphavantage.co/query?function={function}&symbol={symbol}&apikey={api_key}&datatype=json' response = requests.get(url) data = response.json() print(data) 

Data preprocessing Clean and preprocess the data to remove any inconsistencies or missing values, and convert it into a format that can be easily used by machine learning models.
Example: Converting stock data to a pandas DataFrame:

import pandas as pd stock_data = data['Time Series (Daily)'] df = pd.DataFrame(stock_data).T df.head() 

Feature engineering Create meaningful features from the raw data that can help your AI model better understand the stock market's patterns and trends.
Example: Creating moving average and relative strength index (RSI) features:

import numpy as np def moving_average(data, window): return data.rolling(window=window).mean() def relative_strength_index(data, window): delta = data.diff().dropna() gain = delta.where(delta > 0, 0) loss = -delta.where(delta < 0, 0) avg_gain = moving_average(gain, window) avg_loss = moving_average(loss, window) rs = avg_gain / avg_loss rsi = 100 - (100 / (1 + rs)) return rsi df['Close'] = df['4. close'].astype(float) df['MA_20'] = moving_average(df['Close'], 20) df['RSI_14'] = relative_strength_index(df['Close'], 14) 

Building an AI model Choose a simple machine learning model to start with, such as a linear regression or decision tree. As you gain more experience, explore more advanced models like LSTM (Long Short-Term Memory) networks.
Example: Training a linear regression model with scikit-learn:

from sklearn.linear_model import LinearRegression from sklearn.model_selection import train_test_split # Prepare the data features = ['MA_20', 'RSI_14'] target = 'Close' df = df.dropna() X = df[features] y = df[target] # Split the data into train and test sets X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42) # Train the model model = LinearRegression() model.fit(X_train, y_train) 

Evaluating and improving the model Evaluate your model's performance using appropriate metrics, such as Mean Absolute Error (MAE) or Mean Squared Error (MSE). Fine-tune your model by tweaking hyperparameters or trying different algorithms.
Example: Evaluating the model's performance:

from sklearn.metrics import mean_absolute_error # Make predictions y_pred = model.predict(X_test) #Calculate the Mean Absolute Error mae = mean_absolute_error(y_test, y_pred) print(f'Mean Absolute Error: {mae}') 

Implementing a trading strategy
Once you have a reliable model, develop a trading strategy based on the predictions. For example, if the model predicts a stock price increase, you can consider buying, and if it predicts a decrease, you can consider selling.
Example:
Simple trading strategy using AI model predictions:

def simple_trading_strategy(y_true, y_pred, buy_threshold, sell_threshold): actions = [] for i in range(len(y_true)): if y_pred[i] - y_true[i] > buy_threshold: actions.append('Buy') elif y_true[i] - y_pred[i] > sell_threshold: actions.append('Sell') else: actions.append('Hold') return actions actions = simple_trading_strategy(y_test, y_pred, buy_threshold=1, sell_threshold=1) print(actions) 

Backtesting: Backtesting is essential to understand how your strategy would have performed in the past. It helps you fine-tune your strategy and gain confidence in its ability to perform in real-world conditions.
Example: Backtesting the simple trading strategy:
​

def backtest_trading_strategy(y_true, actions): profit = 0 num_stocks = 0 entry_price = 0 for i in range(len(y_true)): if actions[i] == 'Buy' and num_stocks == 0: num_stocks = 1 entry_price = y_true[i] elif actions[i] == 'Sell' and num_stocks > 0: profit += y_true[i] - entry_price num_stocks = 0 return profit profit = backtest_trading_strategy(y_test.values, actions) print(f'Profit from the strategy: {profit}') 

Getting started with AI and big data in trading can be simple and exciting with the right tools and techniques. Follow these steps to build a basic AI-powered trading strategy, and as you gain more experience, experiment with different algorithms and trading strategies to optimize your performance.