by Aabir Abubaker Kar
~1 min read


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  • deep learning classification nlp

Quick summary:

  • What I did:
    • Wrote a Master’s Thesis titled “Common sense reasoning against algorithmic misinformation using Knowledge Graph Embeddings”
    • Led a rotating team of 6 people through multiple projects that culminated in this research design and experimental setup
    • Engineered a Python package weboftruth to train 11 KGE algorithms on any dataset with a single line of code
  • Things I learnt:
    • How to use intuitive representation learning for better algorithmic performance
    • How to build a production-ready deep representation learning pipeline using Python and Torch
    • How to write software for deep learning hardware (cuda, GPUs) etc.
  • When was this?
    • The latter 15 months of my time at UChicago, so May 2020 through September 2021

All code is available at the weboftruth repo. Just python -m pip install git+ to use it.

I also have Jupyter notebooks (accessible via Google Colab) that walk you through the codebase so you can run it yourself.