Speaker: Jakub Chojnacki
Machine Learning Engineer
Dive deep into the world of reinforcement learning with the Ray RLlib library. This comprehensive presentation covers the basics of reinforcement learning, the challenges it presents, and how Ray RLlib can help overcome these obstacles. Discover how to efficiently scale your RL projects from a single laptop to a powerful GPU cluster, and explore the flexibility and power of Ray's ecosystem. Whether you're interested in single-agent or multi-agent systems, model-based approaches, or hyperparameter tuning, this video has something for you.
00:00 Intro & Agenda
00:22 Overview of Reinforcement Learning
02:28 Challenges in Reinforcement Learning
06:56 Multi-Agent Systems & StarCraft Example
09:40 Why Use Ray RLlib?
13:45 Setting Up Ray RLlib
17:50 Using Actors for Distributed Learning
21:05 Applications & Success Stories
#ReinforcementLearning #RayRLlib #MachineLearning #DeepLearning #RL #DataScience
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