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.

Python Data Science Handbook: full text in Jupyter Notebooks

Google Research

Implementing a ChatGPT-like LLM in PyTorch from scratch, step by step

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

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

This repository contains implementations and illustrative code to accompany DeepMind publications

This repository contains demos I made with the Transformers library by HuggingFace.

The "Python Machine Learning (2nd edition)" book code repository and info resource

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

Acceptance rates for the major AI conferences

A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more

A Code-First Introduction to NLP course

Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters

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

About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008

Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch

TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.

Generative Adversarial Networks implemented in PyTorch and Tensorflow

VPoser: Variational Human Pose Prior

Lightweight, useful implementation of conformal prediction on real data.

Data preparation and loader for AMASS

Self-Supervised Learning of 3D Human Pose using Multi-view Geometry (CVPR2019)

Epipolar Transformers (best paper award, CVPR 2020 workshop)

RAD: Reinforcement Learning with Augmented Data

PyTorch Implementation for "TransPose: Keypoint localization via Transformer", ICCV 2021.

Code and website related to the eICU Collaborative Research Database

Conformalized Quantile Regression

A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

All the ML algorithms, ML models are coded from scratch by pure Python/Numpy with the Math under the hood. It works well on CPU.