Udemy - Cutting-Edge AI Deep Reinforcement Learning in Python (10.2022)
File List
- 06 - Setting Up Your Environment (FAQ by Student Request)/001 Anaconda Environment Setup.mp4 175.2 MB
- 04 - DDPG (Deep Deterministic Policy Gradient)/005 DDPG Code (part 1).mp4 124.3 MB
- 03 - A2C (Advantage Actor-Critic)/010 A2C.mp4 116.9 MB
- 06 - Setting Up Your Environment (FAQ by Student Request)/002 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 109.0 MB
- 04 - DDPG (Deep Deterministic Policy Gradient)/004 MuJoCo.mp4 93.5 MB
- 05 - ES (Evolution Strategies)/007 ES for Flappy Bird in Code.mp4 91.4 MB
- 08 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/004 Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 81.2 MB
- 03 - A2C (Advantage Actor-Critic)/008 Environment Wrappers.mp4 80.6 MB
- 08 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/003 Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 75.7 MB
- 07 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/003 Proof that using Jupyter Notebook is the same as not using it.mp4 64.3 MB
- 03 - A2C (Advantage Actor-Critic)/001 A2C Section Introduction.mp4 56.8 MB
- 07 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/001 How to Code by Yourself (part 1).mp4 56.1 MB
- 01 - Welcome/002 Outline.mp4 51.2 MB
- 08 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/002 Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 50.8 MB
- 03 - A2C (Advantage Actor-Critic)/002 A2C Theory (part 1).mp4 49.2 MB
- 03 - A2C (Advantage Actor-Critic)/007 Multiple Processes.mp4 44.7 MB
- 05 - ES (Evolution Strategies)/002 ES Theory.mp4 43.8 MB
- 04 - DDPG (Deep Deterministic Policy Gradient)/006 DDPG Code (part 2).mp4 39.0 MB
- 09 - Appendix FAQ Finale/002 BONUS Lecture.mp4 37.8 MB
- 02 - Review of Fundamental Reinforcement Learning Concepts/003 Markov Decision Processes (MDPs).mp4 36.2 MB
- 05 - ES (Evolution Strategies)/005 ES for Supervised Learning.mp4 35.8 MB
- 01 - Welcome/001 Introduction.mp4 35.8 MB
- 04 - DDPG (Deep Deterministic Policy Gradient)/003 DDPG Theory.mp4 31.7 MB
- 05 - ES (Evolution Strategies)/008 ES for MuJoCo in Code.mp4 30.4 MB
- 02 - Review of Fundamental Reinforcement Learning Concepts/005 Temporal Difference Learning (TD).mp4 30.3 MB
- 03 - A2C (Advantage Actor-Critic)/009 Convolutional Neural Network.mp4 29.5 MB
- 05 - ES (Evolution Strategies)/006 Flappy Bird.mp4 25.3 MB
- 02 - Review of Fundamental Reinforcement Learning Concepts/002 The Explore-Exploit Dilemma.mp4 25.0 MB
- 05 - ES (Evolution Strategies)/003 Notes on Evolution Strategies.mp4 24.8 MB
- 02 - Review of Fundamental Reinforcement Learning Concepts/008 Suggestion Box.mp4 23.3 MB
- 04 - DDPG (Deep Deterministic Policy Gradient)/002 Deep Q-Learning (DQN) Review.mp4 22.3 MB
- 07 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/002 How to Code by Yourself (part 2).mp4 20.9 MB
- 02 - Review of Fundamental Reinforcement Learning Concepts/006 OpenAI Gym Warmup.mp4 20.8 MB
- 05 - ES (Evolution Strategies)/004 ES for Optimizing a Function.mp4 19.2 MB
- 08 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/001 How to Succeed in this Course (Long Version).mp4 16.8 MB
- 03 - A2C (Advantage Actor-Critic)/005 A2C Demo.mp4 16.4 MB
- 05 - ES (Evolution Strategies)/001 ES Section Introduction.mp4 14.2 MB
- 02 - Review of Fundamental Reinforcement Learning Concepts/004 Monte Carlo Methods.mp4 12.8 MB
- 03 - A2C (Advantage Actor-Critic)/003 A2C Theory (part 2).mp4 12.3 MB
- 02 - Review of Fundamental Reinforcement Learning Concepts/007 Review Section Summary.mp4 11.9 MB
- 03 - A2C (Advantage Actor-Critic)/011 A2C Section Summary.mp4 11.6 MB
- 03 - A2C (Advantage Actor-Critic)/006 A2C Code - Rough Sketch.mp4 11.2 MB
- 05 - ES (Evolution Strategies)/009 ES Section Summary.mp4 10.1 MB
- 04 - DDPG (Deep Deterministic Policy Gradient)/001 DDPG Section Introduction.mp4 9.5 MB
- 01 - Welcome/003 Where to get the code.mp4 8.6 MB
- 07 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/004 Python 2 vs Python 3.mp4 7.6 MB
- 02 - Review of Fundamental Reinforcement Learning Concepts/001 Review Section Introduction.mp4 6.9 MB
- 04 - DDPG (Deep Deterministic Policy Gradient)/007 DDPG Section Summary.mp4 6.8 MB
- 03 - A2C (Advantage Actor-Critic)/004 A2C Theory (part 3).mp4 6.2 MB
- 09 - Appendix FAQ Finale/001 What is the Appendix.mp4 6.1 MB
- 08 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/002 Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 31.9 KB
- 03 - A2C (Advantage Actor-Critic)/002 A2C Theory (part 1).srt 26.1 KB
- 02 - Review of Fundamental Reinforcement Learning Concepts/003 Markov Decision Processes (MDPs).srt 25.9 KB
- 05 - ES (Evolution Strategies)/002 ES Theory.srt 25.6 KB
- 04 - DDPG (Deep Deterministic Policy Gradient)/004 MuJoCo.srt 24.1 KB
- 08 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/004 Machine Learning and AI Prerequisite Roadmap (pt 2).srt 23.6 KB
- 04 - DDPG (Deep Deterministic Policy Gradient)/005 DDPG Code (part 1).srt 23.1 KB
- 03 - A2C (Advantage Actor-Critic)/010 A2C.srt 23.0 KB
- 04 - DDPG (Deep Deterministic Policy Gradient)/003 DDPG Theory.srt 22.9 KB
- 07 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/001 How to Code by Yourself (part 1).srt 22.7 KB
- 02 - Review of Fundamental Reinforcement Learning Concepts/005 Temporal Difference Learning (TD).srt 21.6 KB
- 06 - Setting Up Your Environment (FAQ by Student Request)/001 Anaconda Environment Setup.srt 19.8 KB
- 05 - ES (Evolution Strategies)/007 ES for Flappy Bird in Code.srt 17.7 KB
- 02 - Review of Fundamental Reinforcement Learning Concepts/002 The Explore-Exploit Dilemma.srt 17.7 KB
- 08 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/003 Machine Learning and AI Prerequisite Roadmap (pt 1).srt 16.8 KB
- 05 - ES (Evolution Strategies)/006 Flappy Bird.srt 15.4 KB
- 03 - A2C (Advantage Actor-Critic)/008 Environment Wrappers.srt 15.1 KB
- 08 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/001 How to Succeed in this Course (Long Version).srt 14.7 KB
- 06 - Setting Up Your Environment (FAQ by Student Request)/002 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 14.1 KB
- 07 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/003 Proof that using Jupyter Notebook is the same as not using it.srt 14.0 KB
- 07 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/002 How to Code by Yourself (part 2).srt 13.2 KB
- 04 - DDPG (Deep Deterministic Policy Gradient)/002 Deep Q-Learning (DQN) Review.srt 11.9 KB
- 05 - ES (Evolution Strategies)/003 Notes on Evolution Strategies.srt 11.5 KB
- 03 - A2C (Advantage Actor-Critic)/007 Multiple Processes.srt 10.6 KB
- 01 - Welcome/002 Outline.srt 10.5 KB
- 03 - A2C (Advantage Actor-Critic)/001 A2C Section Introduction.srt 10.4 KB
- 02 - Review of Fundamental Reinforcement Learning Concepts/004 Monte Carlo Methods.srt 9.7 KB
- 03 - A2C (Advantage Actor-Critic)/006 A2C Code - Rough Sketch.srt 9.5 KB
- 02 - Review of Fundamental Reinforcement Learning Concepts/007 Review Section Summary.srt 9.3 KB
- 05 - ES (Evolution Strategies)/008 ES for MuJoCo in Code.srt 9.1 KB
- 03 - A2C (Advantage Actor-Critic)/003 A2C Theory (part 2).srt 9.0 KB
- 05 - ES (Evolution Strategies)/001 ES Section Introduction.srt 8.7 KB
- 03 - A2C (Advantage Actor-Critic)/011 A2C Section Summary.srt 8.6 KB
- 02 - Review of Fundamental Reinforcement Learning Concepts/006 OpenAI Gym Warmup.srt 8.2 KB
- 09 - Appendix FAQ Finale/002 BONUS Lecture.srt 7.9 KB
- 05 - ES (Evolution Strategies)/005 ES for Supervised Learning.srt 7.5 KB
- 05 - ES (Evolution Strategies)/004 ES for Optimizing a Function.srt 7.5 KB
- 04 - DDPG (Deep Deterministic Policy Gradient)/006 DDPG Code (part 2).srt 7.0 KB
- 03 - A2C (Advantage Actor-Critic)/009 Convolutional Neural Network.srt 6.8 KB
- 01 - Welcome/003 Where to get the code.srt 6.3 KB
- 05 - ES (Evolution Strategies)/009 ES Section Summary.srt 6.2 KB
- 07 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/004 Python 2 vs Python 3.srt 6.1 KB
- 04 - DDPG (Deep Deterministic Policy Gradient)/007 DDPG Section Summary.srt 5.1 KB
- 02 - Review of Fundamental Reinforcement Learning Concepts/001 Review Section Introduction.srt 5.1 KB
- 01 - Welcome/001 Introduction.srt 5.1 KB
- 02 - Review of Fundamental Reinforcement Learning Concepts/008 Suggestion Box.srt 4.7 KB
- 04 - DDPG (Deep Deterministic Policy Gradient)/001 DDPG Section Introduction.srt 4.4 KB
- 03 - A2C (Advantage Actor-Critic)/004 A2C Theory (part 3).srt 3.8 KB
- 09 - Appendix FAQ Finale/001 What is the Appendix.srt 3.8 KB
- 03 - A2C (Advantage Actor-Critic)/005 A2C Demo.srt 2.8 KB
- 01 - Welcome/003 Github-Link.url 83 bytes
- 01 - Welcome/external-links.txt 80 bytes
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