Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
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Machine learning, in numpy
- machine-learning
- neural-networks
- topic-modeling
- gaussian-mixture-models
An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.
A high-performance distributed training framework for Reinforcement Learning
- reinforcement-learning
- large-scale
- parallelization
Official Repository for "Eureka: Human-Level Reward Design via Coding Large Language Models" (ICLR 2024)
verl-agent is an extension of veRL, designed for training LLM/VLM agents via RL. verl-agent is also the official code for paper "Group-in-Group Policy Optimization for LLM Agent Training"
- llm-agents
- llm-training
- reinforcement-learning
- large-language-models
Humanoid-Gym: Reinforcement Learning for Humanoid Robot with Zero-Shot Sim2Real Transfer https://arxiv.org/abs/2404.05695
- ai
- artificial-intelligence
- control-systems
- humanoid-robot
RoboVerse: Towards a Unified Platform, Dataset and Benchmark for Scalable and Generalizable Robot Learning
- imitation-learning
- reinforcement-learning
- robotics
- simulation
PGPortfolio: Policy Gradient Portfolio, the source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"(https://arxiv.org/pdf/1706.10059.pdf).
A large-scale benchmark and learning environment.
An engine for high performance multi-agent environments with very large numbers of agents, along with a set of reference environments
Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market has experienced significant growth rate and large number of firms are using it. I have tried to build a Deep Q-learning reinforcement agent model to do automated stock trading.