https://huyenchip.com/ml-interviews-book/

A Curated Collection of LLM resources (work in progress).

Get up and running with Llama 3.3, DeepSeek-R1, Phi-4, Gemma 3, and other large language models.

The official Meta Llama 3 GitHub site

A stable copy of Dan Corkill's GBBOpen project.

Python client library for Mistral AI platform

A "large" language model running on a microcontroller

Running Llama 2 and other Open-Source LLMs on CPU Inference Locally for Document Q&A

Repository for the NaLLM project

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

A Python client for the Neo4j Graph Data Science (GDS) library

Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search

Deep Learning for humans

A multi-llm Emacs shell (ChatGPT, Claude, DeepSeek, Gemini, Kagi, Ollama, Perplexity) + editing integrations

The Abstraction and Reasoning Corpus

Inference code for Llama models

Making large AI models cheaper, faster and more accessible

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

A roadmap to learn Kubernetes from scratch (Beginner to Advanced level)

Examples and guides for using the OpenAI API

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

Classical equations and diagrams in machine learning

A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.

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

Exercises for the book Artificial Intelligence: A Modern Approach

aimacode participation in the Google Summer of Code

Lisp code for the textbook "Paradigms of Artificial Intelligence Programming"

An Open Source Machine Learning Framework for Everyone

The Museum of Modern Art (MoMA) exhibitions data

Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"