The official repository which contains the code and pre-trained models for our paper TAPEX: Table Pre-training via Learning a Neural SQL Executor. Use it to navigate the topic and choose relevant methods, papers or tools.

Course materials for General Assembly's Data Science course in Washington, DC (12/15/14 - 3/16/15). Use it to build a structured path from fundamentals to hands-on practice.

The AI Fairness 360 toolkit is an extensible open-source library containing techniques developed by the research community to help detect and mitigate bias in machine learning models throughout the AI application lifecycle. AI Fairness 360 package is available in both Python and. Use it to navigate the topic and choose relevant methods, papers or tools.

Kaolin packages reusable building blocks from NVIDIA 3D research into a cohesive PyTorch API — continuously improving representation-agnostic physics simulation, fast conversions between representations, quaternion math, batched mesh and splat containers, I/O, visualization and m. Use it to build a structured path from fundamentals to hands-on practice.

An interactive deep learning book with code, math, and discussions, based on the NumPy interface by Aston Zhang, Zachary C. Lipton, Mu Li, and Alexander J. Smola. With 900 pages, this seems to be one of the most comprehensive one-stop resources that goes from Linear Neural Networ. Use it to build a structured path from fundamentals to hands-on practice.

First open-source project — fully-local on a single RTX 3090 (Qwen3.6-27B) — to report 95% SimpleQA (n=500) and 77% xbench-DeepSearch (n=100) on local hardware. See the r/LocalLLaMA announcement and the benchmark dataset. Use it as a repeatable review, validation or hardening pass.

This repo has all the resources you need to become an amazing data engineer!. Use it to build a structured path from fundamentals to hands-on practice.