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Achievement: QuickdrawAchievement: YOLOAchievement: Pull Shark

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raghulchandramouli/README.md

What I'm Up To

I read research papers for "fun," try to reimplement them and usually end up debugging my life choices more than my code

  • Currently Learning/doing:
    • Forensics in Generative modeling - "identifying fake images made by fake models trained on fake data, if your wondering its going great or so I say to myself :("
  • Future Plans:
    • Mech Interp - aka Mission Impossible: decoding neural nets before they decode me

Quote I live by: If you don't succeed, blame the author of the paper or its just following the laws of modern ML...

Pinned Loading

  1. pocket_ml pocket_ml Public

    Go to Easy ML Solutions

    Python 1

  2. video_broadcaster video_broadcaster Public

    A go to video-broadcasting service that use OBS to manipulate real-time video

    Python 1

  3. Synthetic-Data-Interpretation Synthetic-Data-Interpretation Public

    This is a Interpretability repo which can generate Fake data via Diffusion, Gans or simply manipulate them via open-CV

    Python 1

  4. Frick_diffseg Frick_diffseg Public

    A deepFake Detection Paper Replication from scratch

    Jupyter Notebook 1

  5. The-Spelled-out-intro-to-Neural-Networks The-Spelled-out-intro-to-Neural-Networks Public

    This contains all the model's I have built watching Andrej Karpathy's zero to Hero series

    Jupyter Notebook