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.

Google Research

Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable…

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…

Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding). Translations: 🇺🇸 🇨🇳 🇯🇵 🇮🇹 🇰🇷 🇷🇺 🇧🇷 🇪🇸

This repository contains the source code for the paper First Order Motion Model for Image Animation

A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API

Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

Public facing notes page

🤖 💬 Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)

A collection of pre-trained, state-of-the-art models in the ONNX format

Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

Playing Pokemon Red with Reinforcement Learning

Inpaint anything using Segment Anything and inpainting models.

Flax is a neural network library for JAX that is designed for flexibility.

An annotated implementation of the Transformer paper.

A scikit-learn compatible neural network library that wraps PyTorch

Repo for the Deep Reinforcement Learning Nanodegree program

Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch

Solve puzzles. Improve your pytorch.

Bayesian optimization in PyTorch

Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL

Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)

An Interactive Introduction to Fourier Transforms

An interactive book on deep learning. Much easy, so MXNet. Wow. [Straight Dope is growing up] ---> Much of this content has been incorporated into the new Dive into Deep Learning Book available at …

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

Handout for the tutorial "Creating publication-quality figures with matplotlib"

subpixel: A subpixel convnet for super resolution with Tensorflow