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Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

AI's query engine - Platform for building AI that can learn and answer questions over federated data.

Documentation that simply works

Turns Data and AI algorithms into production-ready web applications in no time.

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

Network Analysis in Python

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

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

Official repository for Spyder - The Scientific Python Development Environment

An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)

🛡️ Windows Hello™ style facial authentication for Linux

Emulator for rapid prototyping of Software Defined Networks

Solving the Traveling Salesman Problem using Self-Organizing Maps

Computer Networks: A Systems Approach -- Textbook

Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning

rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.

A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.

A minimalist environment for decision-making in autonomous driving

Eclipse SUMO is an open source, highly portable, microscopic and continuous traffic simulation package designed to handle large networks. It allows for intermodal simulation including pedestrians a…

Collection of reinforcement learning algorithms

A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.

Python Multi-Agent Reinforcement Learning framework

A collection of reference environments for offline reinforcement learning

The can package provides controller area network support for Python developers

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

Computational framework for reinforcement learning in traffic control

Soft Actor-Critic

Fast & Simple Resource-Constrained Learning of Deep Network Structure