Kickstart your MLOps initiative with a flexible, robust, and productive Python package.

Kickstart your LLMOps initiative with a flexible, robust, and productive Python package.

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

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

Efficient vision foundation models for high-resolution generation and perception.

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…

A playbook for systematically maximizing the performance of deep learning models.

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

Community Discovery Library

High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings.

Python package built to ease deep learning on graph, on top of existing DL frameworks.

Some useful tips for faiss

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…

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

The Patterns of Scalable, Reliable, and Performant Large-Scale Systems

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

Curated list of project-based tutorials

🔗 Some useful websites for programmers.

Interactive roadmaps, guides and other educational content to help developers grow in their careers.