Day-17-Reinforcement Learning in Machine Learning

📚 Topics Covered

✅ Introduction to Reinforcement Learning
✅ Three Types of Machine Learning
✅ Key Components of RL
✅ The RL Interaction Loop
✅ Real-Life Analogy: Training a Dog
✅ Markov Decision Process (MDP)
✅ Value Functions (V and Q)
✅ Bellman Equation
✅ Q-Learning Algorithm
✅ Q-Learning from Scratch in Python
✅ Deep Q-Network (DQN)
✅ Policy Gradient Methods
✅ Actor-Critic Architecture
✅ Gymnasium & Stable-Baselines3
✅ Reinforcement Learning from Human Feedback (RLHF)
✅ How ChatGPT Uses RLHF
✅ Famous RL Achievements (AlphaGo, OpenAI Five, AlphaStar)
✅ Advantages & Limitations
✅ Real-World Applications
✅ Interview Questions
✅ Summary

Видео Day-17-Reinforcement Learning in Machine Learning канала AI & ML META