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jyot_makadiya
Jyot Makadiya

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Ahmedabad, IN

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A benchmark for image-based food recognition

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failed 172443
failed 172394
failed 172379

ASCII-rendered single-player dungeon crawl game

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graded 158643

Machine Learning for detection of early onset of Alzheimers

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graded 144118
graded 144116
failed 144113

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Measure sample efficiency and generalization in reinforcement learning using procedurally generated environments

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3D Seismic Image Interpretation by Machine Learning

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graded 160590
graded 159739
graded 159738

5 Puzzles 21 Days. Can you solve it all?

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graded 154211

Play in a realistic insurance market, compete for profit!

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5 Puzzles 21 Days. Can you solve it all?

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graded 151377

Multi-Agent Reinforcement Learning on Trains

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A dataset and open-ended challenge for music recommendation research

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Sample-efficient reinforcement learning in Minecraft

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Project 2: build our own text classifier system, and test its performance.

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Multi-Agent Reinforcement Learning on Trains

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ADDI Alzheimers Detection Challenge

🚨 Final Leaderboard (for real) + Community Contribution Prize

Almost 3 years ago

Congratulations to all the winners!! Hope to see you all in the next competition!!

Final leaderboard not visible

Almost 3 years ago

After waiting for the whole day:
image

Final leaderboard not visible

Almost 3 years ago

Thanks for the info, can’t wait to see the final leaderboard and winners’ solutions!!

Random variable(s)

Almost 3 years ago

Hello @demarsylvain,
TLDR: My experiments were somewhat different than yours but the conclusion is similar that data contains some noise/random variables which plays a big role in predictions.
I first tried with raw features and minimal pre-processing, then with heavy feature engineering (around 8-10 features were added), and finally experimented with removing unnecessary features. The results were shockingly similar and unintuitive to me. My raw features model performs almost similar to the heavy feature engineered model and minimal features model. The same data with slight changes leads to a drastic difference in log loss (kinda butterfly effect), therefore I think it’s the case of random variable majorly impacting the results. I hope this helps.

That golden feature... were we supposed to have it?

Almost 3 years ago

Hello @michael_bordeleau,
I think the feature is used to extract training labels, for example, it might be possible that the 0-5 scale feature is then scaled accordingly to 0-2 ( Normal, Pre-Alzheimers, post-Alzheimers) with some other data to get labels. It may be one of the reasons, i.e, fear of data leak in this competition. This is still my guess, I am not sure. Also thanks for your contributions, I learned a lot from your posts.
Jyot

Submission time

Almost 3 years ago

Hello @HarryDing, To install any browser, you have to upload the corresponding installer (in Windows VM.exe) from your local computer. I installed firefox this way, also make sure that you upload the complete installer .exe which works offline not the installer that downloads the files from the internet while executing. I spent a lot of time trying to install Firefox, hope this helps.

Submission time

Almost 3 years ago

Hello @HarryDing, this has happened to me once in Windows VM, I found that simply rerun all the cells after reconnecting to that notebook kernel will resolve this issue. Alternatively, you can restart the jupyter-lab instance.

Couldn't decode response from AIcrowd servers

Almost 3 years ago

This thread is funny! I think we need a dedicated meme thread for the competition! All the best!!

Common issues for Windows users

Almost 3 years ago

Hello @jyotish, actually I tried that earlier, and it doesn’t work for me. I have to open new prompt and set up proxies. Then after I can install using pip install x . I found that it is setting temporary proxies for one session I guess.

Common issues for Windows users

Almost 3 years ago

Thanks, @jyotish and @nrad for helping me. It worked and I was able to successfully run the magic command. I am curious that I need to set all 3 proxies every time I open a new Anaconda Prompt. Any suggestion on how I can set universal or global proxies for that?

Common issues for Windows users

Almost 3 years ago

Hello @nrad, first of all, thank you for all your efforts and hard work. I have completed the windows VM setup and got the starter notebook. However I am stuck on the %load_ext aicrowd.magic cell when tried to run, it generates error like this:
Import Error: failed to initialize: Bad git executable.
To check the issue, I tried running the pip command on the Anaconda prompt and there I saw that the pip was working there too. I have checked my proxy internet which is working fine as I was able to open pypi.python.org but in jupyter-notebook or anaconda prompt, I couldn’t make the second command work. Also, I tried restarting VM and ensuring that the starter script completes execution. It would be helpful if you can guide me on the issue.
Thanks!

CS grad getting experience in DL/ML.

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