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Course content
- Practical Reinforcement Learning – Agents and Environments
- Advanced Practical Reinforcement Learning
- Hands-On Deep Q-Learning
- Reinforcement Learning with TensorFlow & TRFL
Course content
- Get Started
- Bias-Variance Trade-Off
- Bootstrap Estimates and Bagging
- Random Forest
- AdaBoost
- Background Review
- Setting Up Your Environment (FAQ by Student Request)
- Extra Help With Python Coding for Beginners (FAQ by Student Request)
- Effective Learning Strategies for Machine Learning (FAQ by Student Request)
- Appendix / FAQ Finale
