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  • London

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Efesasa0/README.md

I write in mostly python for AI and ML projects. The project building flow goes like follows:

  1. Get interested at a random thing.
  2. Let it sink in for few days.
  3. Revisit and do preliminary research take notes.
  4. Check out what people have already built if any.
  5. Start building myself.
  6. Complete documentation based on notes and push.
  7. Adios, maybe I'll be back.

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  1. carvana-unet carvana-unet Public

    Unet implementation using PyTorch | Carvana Segmentation

    Jupyter Notebook

  2. GDZ-elektrik-timeseries GDZ-elektrik-timeseries Public

    An attempt to implement an AutoML around xgb, catboost and lightgbm

    Python 3 1

  3. auto-encoder-maze auto-encoder-maze Public

    EE456 final project exploring the Auto Encoder CNN architecture in 2022.

    Jupyter Notebook

  4. real-time-speech-translation real-time-speech-translation Public

    Audio recoding and translation service in realtime

    Python

  5. smooth-life smooth-life Public

    Smooth and continuous version of Convay's game of life implemented using python

    Jupyter Notebook

  6. diffusion-image-generation diffusion-image-generation Public

    Jupyter Notebook