[WIP] Resources for AI engineers. Also contains supporting materials for the book AI Engineering (Chip Huyen, 2025)

The awesome and classic papers in recommendation system!!! Good luck to every RecSys-learner!

Course 18.S191 at MIT, Fall 2022 - Introduction to computational thinking with Julia

Statistical Rethinking Course Winter 2020/2021

A collection of algorithms and data structures

The Metadata Platform for your Data and AI Stack

Convert an HTML file of book notes exported from an Amazon Kindle to a Markdown document

All Algorithms implemented in Python

Notebooks for the "A walk with fastai2" Study Group and Lecture Series

A curated list of blogs for curious people

Bayesian Data Analysis course at Aalto

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

Reinforcement learning resources curated

A library of sklearn compatible categorical variable encoders

Fit interpretable models. Explain blackbox machine learning.

Curating a list of AutoML-related research, tools, projects and other resources

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

⭕️ Data Engineering for Data Scientists

Bias Auditing & Fair ML Toolkit

Deep Learning with TensorFlow, Keras, and PyTorch

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Python programs, usually short, of considerable difficulty, to perfect particular skills.

Materials for class Getting Started with Pyspark

Notebooks about Bayesian methods for machine learning

Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas

The 3rd edition of course.fast.ai

A game theoretic approach to explain the output of any machine learning model.

Tutorial for International Summer School on Deep Learning, 2019