Deep Reinforcement Learning | UC Berkeley CS 285

Dive into the latest advancements in deep reinforcement learning with hands-on experience and expert guidance from UC Berkeley's CS 285 course.

Introduction

CS285 is a course on deep reinforcement learning offered at UC Berkeley. It covers the fundamental concepts and algorithms in deep reinforcement learning, including policy gradients, value function approximation, and model-based methods.

Highlights

• Covers the latest advancements in deep reinforcement learning
• Hands-on experience with implementing deep RL algorithms
• Taught by leading experts in the field of deep reinforcement learning

Recommendation

This course is recommended for students and researchers interested in the field of deep reinforcement learning. It provides a solid foundation in the theory and practical application of deep RL, and is suitable for those with a background in machine learning and programming.

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