Google Research

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

This is a repo with links to everything you'd ever want to learn about data engineering

A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

A collection of infrastructure and tools for research in neural network interpretability.

Material for gpu-mode lectures

Learn how to design, develop, deploy and iterate on production-grade ML applications.

A python library for decision tree visualization and model interpretation.

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.

Multivariate Time Series Forecasting with efficient Transformers. Code for the paper "Long-Range Transformers for Dynamic Spatiotemporal Forecasting."

Current and Historical Lists of S&P 500 components since 1996

Factorization Machine for regression and classification

Cell and line magic for PGF/TikZ-to-SVG rendering in Jupyter notebooks

Package implementing Convergent Cross Mapping for causality inference in dynamical systems

Julia for Data Science - Tippie Graduate Analytics Workshop, University of Iowa