Udemy - Advanced AI: Deep Reinforcement Learning in Python

Files:

• 1. Introduction and Outline.mp4 (15.8 MB)
• 1. Introduction and Outline.vtt (12.8 KB)
• 2. Where to get the Code.mp4 (5.2 MB)
• 2. Where to get the Code.vtt (4.1 KB)
• 3. How to Succeed in this Course.mp4 (3.3 MB)
• 3. How to Succeed in this Course.vtt (3.5 KB)
• 4. Tensorflow or Theano - Your Choice!.mp4 (18.9 MB)
• 4. Tensorflow or Theano - Your Choice!.vtt (4.8 KB)

• 1. Review Intro.mp4 (4.2 MB)
• 1. Review Intro.vtt (3.1 KB)
• 2. Review of Markov Decision Processes.mp4 (12.3 MB)
• 2. Review of Markov Decision Processes.vtt (8.9 KB)
• 3. Review of Dynamic Programming.mp4 (6.5 MB)
• 3. Review of Dynamic Programming.vtt (4.7 KB)
• 4. Review of Monte Carlo Methods.mp4 (6.2 MB)
• 4. Review of Monte Carlo Methods.vtt (4.4 KB)
• 5. Review of Temporal Difference Learning.mp4 (7.2 MB)
• 5. Review of Temporal Difference Learning.vtt (5.2 KB)
• 6. Review of Approximation Methods for Reinforcement Learning.mp4 (3.7 MB)
• 6. Review of Approximation Methods for Reinforcement Learning.vtt (2.5 KB)
• 7. Review of Deep Learning.mp4 (11.0 MB)
• 7. Review of Deep Learning.vtt (8.2 KB)

• 1. OpenAI Gym Tutorial.mp4 (8.7 MB)
• 1. OpenAI Gym Tutorial.vtt (6.8 KB)
• 10. Theano Warmup.mp4 (5.8 MB)
• 10. Theano Warmup.vtt (3.1 KB)
• 11. Tensorflow Warmup.mp4 (5.1 MB)
• 11. Tensorflow Warmup.vtt (2.2 KB)
• 12. Plugging in a Neural Network.mp4 (5.9 MB)
• 12. Plugging in a Neural Network.vtt (4.3 KB)
• 13. OpenAI Gym Section Summary.mp4 (5.3 MB)
• 13. OpenAI Gym Section Summary.vtt (3.7 KB)
• 2. Random Search.mp4 (10.3 MB)
• 2. Random Search.vtt (6.0 KB)
• 3. Saving a Video.mp4 (4.5 MB)
• 3. Saving a Video.vtt (2.1 KB)
• 4. CartPole with Bins (Theory).mp4 (6.0 MB)
• 4. CartPole with Bins (Theory).vtt (4.6 KB)
• 5. CartPole with Bins (Code).mp4 (14.7 MB)
• 5. CartPole with Bins (Code).vtt (7.0 KB)
• 6. RBF Neural Networks.mp4 (16.5 MB)
• 6. RBF Neural Networks.vtt (12.8 KB)
• 7. RBF Networks with Mountain Car (Code).mp4 (13.7 MB)
• 7. RBF Networks with Mountain Car (Code).vtt (5.7 KB)
• 8. RBF Networks with CartPole (Theory).mp4 (3.1 MB)
• 8. RBF Networks with CartPole (Theory).vtt (2.2 KB)
• 9. RBF Networks with CartPole (Code).mp4 (8.9 MB)
• 9. RBF Networks with CartPole (Code).vtt (3.2 KB)

• 1. N-Step Methods.mp4 (5.0 MB)
• 1. N-Step Methods.vtt (3.4 KB)
• 2. N-Step in Code.mp4 (9.5 MB)
• 2. N-Step in Code.vtt (3.7 KB)
• 3. TD Lambda.mp4 (11.8 MB)
• 3. TD Lambda.vtt (8.2 KB)
• 4. TD Lambda in Code.mp4 (7.6 MB)
• 4. TD Lambda in Code.vtt (2.9 KB)
• 5. TD Lambda Summary.mp4 (3.6 MB)
• 5. TD Lambda Summary.vtt (2.6 KB)

• 1. Policy Gradient Methods.mp4 (18.0 MB)
• 1. Policy Gradient Methods.vtt (13.0 KB)
• 10. Policy Gradient Section Summary.mp4 (3.3 MB)
• 10. Policy Gradient Section Summary.vtt (1.7 KB)
• 2. Policy Gradient in TensorFlow for CartPole.mp4 (18.0 MB)
• 2. Policy Gradient in TensorFlow for CartPole.vtt (7.7 KB)
• 3. Policy Gradient in Theano for CartPole.mp4 (13.4 MB)
• 3. Policy Gradient in Theano for CartPole.vtt (4.0 KB)
• 4. Continuous Action Spaces.mp4 (6.6 MB)
• 4. Continuous Action Spaces.vtt (4.7 KB)
• 5. Mountain Car Continuous Specifics.mp4 (6.5 MB)
• 5. Mountain Car Continuous Specifics.vtt (4.4 KB)
• 6. Mountain Car Continuous Theano.mp4 (19.1 MB)
• 6. Mountain Car Continuous Theano.vtt (8.6 KB)
• 7. Mountain Car Continuous Tensorflow.mp4 (20.1 MB)
• 7. Mountain Car Continuous Tensorflow.vtt (9.0 KB)
• 8. Mountain Car Continuous Tensorflow (v2).mp4 (18.8 MB)
• 8. Mountain Car Continuous Tensorflow (v2).vtt (6.2 KB)
• 9. Mountain Car Continuous Theano (v2).mp4 (22.2 MB)
• 9. Mountain Car Continuous Theano (v2).vtt (7.4 KB)

• 1. Deep Q-Learning Intro.mp4 (5.9 MB)
• 1. Deep Q-Learning Intro.vtt (4.2 KB)
• 2. Deep Q-Learning Techniques.mp4 (14.5 MB)
• 2. Deep Q-Learning Techniques.vtt (10.8 KB)
• 3. Deep Q-Learning in Tensorflow for CartPole.mp4 (15.0 MB)
• 3. Deep Q-Learning in Tensorflow for CartPole.vtt (5.1 KB)
• 4. Deep Q-Learning in Theano for CartPole.mp4 (13.8 MB)
• 4. Deep Q-Learning in Theano for CartPole.vtt (4.8 KB)
• 5. Additional Implementation Details for Atari.mp4 (8.5 MB)
• 5. Additional Implementation Details for Atari.vtt (6.2 KB)
• 6. Deep Q-Learning in Tensorflow for Breakout.mp4 (15.8 MB)
• 6. Deep Q-Learning in Tensorflow for Breakout.vtt (6.1 KB)
• 7. Deep Q-Learning in Theano for Breakout.mp4 (20.0 MB)
• 7. Deep Q-Learning in Theano for Breakout.vtt (7.1 KB)
• 8. Partially Observable MDPs.mp4 (7.6 MB)
• 8. Partially Observable MDPs.vtt (5.1 KB)
• 9. Deep Q-Learning Section Summary.mp4 (10.4 MB)
• 9. Deep Q-Learning Section Summary.vtt (5.3 KB)

• 1. A3C - Theory and Outline.mp4 (71.8 MB)
• 1. A3C - Theory and Outline.vtt (17.9 KB)
• 2. A3C - Code pt 1 (Warmup).mp4 (50.1 MB)
• 2. A3C - Code pt 1 (Warmup).vtt (6.8 KB)
• 3. A3C - Code pt 2.mp4 (57.6 MB)
• 3. A3C - Code pt 2.vtt (7.3 KB)
• 4. A3C - Code pt 3.mp4 (84.5 MB)
• 4. A3C - Code pt 3.vtt (8.0 KB)
• 5. A3C - Code pt 4.mp4 (184.4 MB)

• Code:

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