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gaugup/README.md

Hi, I'm Gaurav Gupta 👋

Building systems that connect language to knowledge at scale

Senior Machine Learning Engineer at Microsoft AI, working on entity linking and knowledge graph integration for Microsoft Bing, connecting unstructured queries to structured entities at web scale.

What I Work On

  • Search & NLP — Entity linking and knowledge graph systems for Microsoft Bing at web scale
  • Responsible AI — Previously a core contributor to responsible-ai-toolbox and DiCE (counterfactual explanations for ML models)
  • ML Infrastructure — Building unified interfaces for ML frameworks (ml-wrappers)
  • Open Source — Shipping production-grade tools used by thousands of data scientists and engineers

Publications & Patents

Writing

I write about software testing, ML engineering, and developer productivity on Medium.

Tech Stack

Python · NLP · Knowledge Graphs · Azure ML · TypeScript · scikit-learn · PyTorch · pytest · Git

Connect

LinkedIn Medium

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  1. interpretml/DiCE interpretml/DiCE Public

    Generate Diverse Counterfactual Explanations for any machine learning model.

    Python 1.5k 230

  2. microsoft/responsible-ai-toolbox microsoft/responsible-ai-toolbox Public

    Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and l…

    TypeScript 1.8k 477

  3. microsoft/ml-wrappers microsoft/ml-wrappers Public

    A unified wrapper for various ML frameworks - to have one uniform scikit-learn format for predict and predict_proba functions.

    Python 49 17

  4. scikit-learn-contrib/imbalanced-learn scikit-learn-contrib/imbalanced-learn Public

    A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

    Python 7.1k 1.3k

  5. interpretml/interpret-community interpretml/interpret-community Public

    Interpret Community extends Interpret repository with additional interpretability techniques and utility functions to handle real-world datasets and workflows.

    Python 443 88