Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

Reactive API for creating calendar events in iOS

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Putting TensorFlow back in PyTorch, back in TensorFlow (differentiable TensorFlow PyTorch adapters).

A Repository with C implementations of Reinforcement Learning Algorithms (Pytorch)

NumPy aware dynamic Python compiler using LLVM

💯 Curated coding interview preparation materials for busy software engineers

OpenAI Scholar, general materials

A curated list of awesome responsible machine learning resources.

A library for real-time video stream decoding to CUDA memory

Composable transformations of Python NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.

Code samples for Back to Back SWE lessons (archive).

VIP cheatsheets for Stanford's CS 229 Machine Learning

This repository contains an introduction to deep learning models implemented in numpy and pytorch.

StyleGAN - Official TensorFlow Implementation

Implementation of the supervised learning experiments in Vector-based navigation using grid-like representations in artificial agents, as published at https://www.nature.com/articles/s41586-018-0102-6

An Open Source Machine Learning Framework for Everyone

Spaced repetition through deep reinforcement learning

This repository contains the implementation for the paper - Exploration via Hierarchical Meta Reinforcement Learning.

Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.

Simple and easily configurable grid world environments for reinforcement learning

This repository contains the code for the implementation of the disentangled map representation in pytorch.

Simple examples to introduce PyTorch

This repository contains the implementation for Model Agnostic Variational Exploration.

Reinforcement Learning with Model-Agnostic Meta-Learning in Pytorch

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

Code for the paper "Exploration by Random Network Distillation"

Tensorflow implementation for Empowerment driven Exploration using Mutual Information Estimation