Google Research

The fastai deep learning library

Natural Language Processing Tutorial for Deep Learning Researchers

PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)

Code release for NeRF (Neural Radiance Fields)

YSDA course in Natural Language Processing

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

TensorFlow Tutorials with YouTube Videos

A real-time approach for mapping all human pixels of 2D RGB images to a 3D surface-based model of the body

A scikit-learn compatible neural network library that wraps PyTorch

Reference models and tools for Cloud TPUs.

The 3rd edition of course.fast.ai

Go to https://github.com/pytorch/tutorials - this repo is deprecated and no longer maintained

Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning

Single Shot MultiBox Detector in TensorFlow

Tutorials for creating and using ONNX models

Debugging, monitoring and visualization for Python Machine Learning and Data Science

Bayesian optimization in PyTorch

VISSL is FAIR's library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.

2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

Code for Stanford CS224u

Discovering Interpretable GAN Controls [NeurIPS 2020]

Official Repository for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]

An out-of-box human parsing representation extractor.

This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CNPs), Neural Processes (NPs), Attentive Neural Processes (ANPs).

Code for paper "Which Training Methods for GANs do actually Converge? (ICML 2018)"

Flowtron is an auto-regressive flow-based generative network for text to speech synthesis with control over speech variation and style transfer

Multi Task Vision and Language

The source code for paper "Deep Image Spatial Transformation for Person Image Generation"

Efficient Learning of Augmentation Policy Schedules