Udemy - Advanced AI: Deep Reinforcement Learning in Python

Files:

• 1. Introduction and Outline.mp4 (50.5 MB)
• 1. Introduction and Outline.srt (11.3 KB)
• 2. Where to get the Code.mp4 (51.6 MB)
• 2. Where to get the Code.srt (13.2 KB)
• 2.1 Github Link.html (0.1 KB)
• 3. How to Succeed in this Course.mp4 (43.8 MB)
• 3. How to Succeed in this Course.srt (8.3 KB)
• 4. Tensorflow or Theano - Your Choice!.mp4 (18.9 MB)
• 4. Tensorflow or Theano - Your Choice!.srt (5.4 KB)
• [Tutorialsplanet.NET].url (0.1 KB)

• 1. How to Code by Yourself (part 1).mp4 (24.5 MB)
• 1. How to Code by Yourself (part 1).srt (22.8 KB)
• 2. How to Code by Yourself (part 2).mp4 (14.8 MB)
• 2. How to Code by Yourself (part 2).srt (13.3 KB)
• 3. Proof that using Jupyter Notebook is the same as not using it.mp4 (78.3 MB)
• 3. Proof that using Jupyter Notebook is the same as not using it.srt (14.1 KB)
• 4. Python 2 vs Python 3.mp4 (7.8 MB)
• 4. Python 2 vs Python 3.srt (6.1 KB)
• 5. Is Theano Dead.mp4 (17.8 MB)
• 5. Is Theano Dead.srt (12.9 KB)
• [Tutorialsplanet.NET].url (0.1 KB)

• 1. How to Succeed in this Course (Long Version).mp4 (18.3 MB)
• 1. How to Succeed in this Course (Long Version).srt (14.5 KB)
• 2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 (0.0 KB)
• 2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt (0.0 KB)
• 3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 (29.3 MB)
• 3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt (16.0 KB)
• 4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 (37.6 MB)
• 4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt (23.0 KB)

• 1. What is the Appendix.mp4 (5.5 MB)
• 1. What is the Appendix.srt (3.7 KB)
• 2. BONUS.mp4 (37.9 MB)
• 2. BONUS.srt (7.9 KB)

• 1. Reinforcement Learning Section Introduction.mp4 (41.0 MB)
• 1. Reinforcement Learning Section Introduction.srt (8.8 KB)
• 10. Epsilon-Greedy.mp4 (40.2 MB)
• 10. Epsilon-Greedy.srt (7.5 KB)
• 11. Q-Learning.mp4 (67.1 MB)
• 11. Q-Learning.srt (19.0 KB)
• 12. How to Learn Reinforcement Learning.mp4 (40.6 MB)
• 12. How to Learn Reinforcement Learning.srt (7.8 KB)
• 13. Suggestion Box.mp4 (16.1 MB)
• 13. Suggestion Box.srt (4.7 KB)
• 2. Elements of a Reinforcement Learning Problem.mp4 (105.2 MB)
• 2. Elements of a Reinforcement Learning Problem.srt (27.1 KB)
• 3. States, Actions, Rewards, Policies.mp4 (44.5 MB)
• 3. States, Actions, Rewards, Policies.srt (11.7 KB)
• 4. Markov Decision Processes (MDPs).mp4 (50.9 MB)
• 4. Markov Decision Processes (MDPs).srt (13.3 KB)
• 5. The Return.mp4 (23.8 MB)
• 5. The Return.srt (6.7 KB)
• 6. Value Functions and the Bellman Equation.mp4 (48.1 MB)
• 6. Value Functions and the Bellman Equation.srt (12.8 KB)
• 7. What does it mean to “learn”.mp4 (31.8 MB)
• 7. What does it mean to “learn”.srt (8.9 KB)
• 8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4 (42.9 MB)
• 8. Solving the Bellman Equation with Reinforcement Learning (pt 1).srt (12.4 KB)
• 9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4 (57.3 MB)
• 9. Solving the Bellman Equation with Reinforcement Learning (pt 2).srt (15.5 KB)

• 1. OpenAI Gym Tutorial.mp4 (8.7 MB)
• 1. OpenAI Gym Tutorial.srt (7.7 KB)
• 10. Theano Warmup.mp4 (5.8 MB)
• 10. Theano Warmup.srt (3.5 KB)
• 11. Tensorflow Warmup.mp4 (5.1 MB)
• 11. Tensorflow Warmup.srt (2.5 KB)
• 12. Plugging in a Neural Network.mp4 (5.9 MB)
• 12. Plugging in a Neural Network.srt (4.8 KB)
• 13. OpenAI Gym Section Summary.mp4 (5.3 MB)
• 13. OpenAI Gym Section Summary.srt (4.2 KB)
• 2. Random Search.mp4 (10.3 MB)
• 2. Random Search.srt (6.9 KB)
• 3. Saving a Video.mp4 (4.5 MB)
• 3. Saving a Video.srt (2.4 KB)
• 4. CartPole with Bins (Theory).mp4 (6.0 MB)
• 4. CartPole with Bins (Theory).srt (5.2 KB)
• 5. CartPole with Bins (Code).mp4 (14.7 MB)
• 5. CartPole with Bins (Code).srt (8.0 KB)
• 6. RBF Neural Networks.mp4 (16.5 MB)
• 6. RBF Neural Networks.srt (14.6 KB)
• 7. RBF Networks with Mountain Car (Code).mp4 (13.8 MB)
• 7. RBF Networks with Mountain Car (Code).srt (6.4 KB)
• 8. RBF Networks with CartPole (Theory).mp4 (3.1 MB)
• 8. RBF Networks with CartPole (Theory).srt (2.4 KB)
• 9. RBF Networks with CartPole (Code).mp4 (8.9 MB)
• 9. RBF Networks with CartPole (Code).srt (3.6 KB)

• 1. N-Step Methods.mp4 (15.6 MB)
• 1. N-Step Methods.srt (3.8 KB)
• 2. N-Step in Code.mp4 (9.5 MB)
• 2. N-Step in Code.srt (4.2 KB)
• 3. TD Lambda.mp4 (11.8 MB)
• 3. TD Lambda.srt (9.3 KB)
• 4. TD Lambda in Code.mp4 (7.6 MB)
• 4. TD Lambda in Code.srt (3.3 KB)
• 5. TD Lambda Summary.mp4 (3.6 MB)
• 5. TD Lambda Summary.srt (3.0 KB)

• 1. Policy Gradient Methods.mp4 (17.9 MB)
• 1. Policy Gradient Methods.srt (14.8 KB)
• 10. Policy Gradient Section Summary.mp4 (3.3 MB)
• 10. Policy Gradient Section Summary.srt (1.9 KB)
• 2. Policy Gradient in TensorFlow for CartPole.mp4 (18.0 MB)
• 2. Policy Gradient in TensorFlow for CartPole.srt (8.7 KB)
• 3. Policy Gradient in Theano for CartPole.mp4 (13.4 MB)
• 3. Policy Gradient in Theano for CartPole.srt (4.5 KB)
• 4. Continuous Action Spaces.mp4 (6.6 MB)
• 4. Continuous Action Spaces.srt (5.3 KB)
• 5. Mountain Car Continuous Specifics.mp4 (6.5 MB)
• 5. Mountain Car Continuous Specifics.srt (5.0 KB)
• 6. Mountain Car Continuous Theano.mp4 (19.1 MB)
• 6. Mountain Car Continuous Theano.srt (9.9 KB)
• 7. Mountain Car Continuous Tensorflow.mp4 (20.1 MB)
• 7. Mountain Car Continuous Tensorflow.srt (10.3 KB)
• 8. Mountain Car Continuous Tensorflow (v2).mp4 (18.8 MB)
• 8. Mountain Car Continuous Tensorflow (v2).srt (7.1 KB)
• 9. Mountain Car Continuous Theano (v2).mp4 (22.2 MB)
• 9. Mountain Car Continuous Theano (v2).srt (8.3 KB)

• 1. Deep Q-Learning Intro.mp4 (5.9 MB)
• 1. Deep Q-Learning Intro.srt (4.8 KB)
• 10. Deep Q-Learning Section Summary.mp4 (10.4 MB)
• 10. Deep Q-Learning Section Summary.srt (6.0 KB)
• 2. Deep Q-Learning Techniques.mp4 (14.4 MB)
• 2. Deep Q-Learning Techniques.srt (12.3 KB)
• 3. Deep Q-Learning in Tensorflow for CartPole.mp4 (15.0 MB)
• 3. Deep Q-Learning in Tensorflow for CartPole.srt (5.8 KB)
• 4. Deep Q-Learning in Theano for CartPole.mp4 (13.8 MB)
• 4. Deep Q-Learning in Theano for CartPole.srt (5.4 KB)
• 5. Additional Implementation Details for Atari.mp4 (8.5 MB)
• 5. Additional Implementation Details for Atari.srt (7.0 KB)
• 6. Pseudocode and Replay Memory.mp4 (27.8 MB)
• 6. Pseudocode and Replay Memory.srt (7.8 KB)
• 7. Deep Q-Learning in Tensorflow for Breakout.mp4 (234.6 MB)
• 7. Deep Q-Learning in Tensorflow for Breakout.srt (28.2 KB)
• 8. Deep Q-Learning in Theano for Breakout.mp4 (233.7 MB)
• 8. Deep Q-Learning in Theano for Breakout.srt (28.1 KB)
• 9. Partially Observable MDPs.mp4 (7.6 MB)
• 9. Partially Observable MDPs.srt (5.8 KB)

• 1. A3C - Theory and Outline.mp4 (71.8 MB)
• 1. A3C - Theory and Outline.srt (20.3 KB)
• 2. A3C - Code pt 1 (Warmup).mp4 (50.1 MB)
• 2. A3C - Code pt 1 (Warmup).srt (7.8 KB)
• 3. A3C - Code pt 2.mp4 (57.6 MB)
• 3. A3C - Code pt 2.srt (8.3 KB)
• 4. A3C - Code pt 3.mp4 (84.5 MB)
• 4. A3C - Code pt 3.srt (9.0 KB)
• 5. A3C - Code pt 4.mp4 (184.3 MB)
• 5. A3C - Code pt 4.srt (21.2 KB)
• 6. A3C - Section Summary.mp4 (8.9 MB)
• 6. A3C - Section Summary.srt (2.6 KB)
• 7. Course Summary.mp4 (9.4 MB)
• 7. Course Summary.srt (6.0 KB)

• 1. (Review) Theano Basics.mp4 (78.1 MB)
• 1. (Review) Theano Basics.srt (7.3 KB)
• 2. (Review) Theano Neural Network in Code.mp4 (67.7 MB)
• 2. (Review) Theano Neural Network in Code.srt (3.9 KB)
• 3. (Review) Tensorflow Basics.mp4 (63.4 MB)
• 3. (Review) Tensorflow Basics.srt (6.0 KB)
• 4. (Review) Tensorflow Neural Network in Code.mp4 (78.4 MB)
• 4. (Review) Tensorflow Neural Network in Code.srt (6.0 KB)

• 1. Anaconda Environment Setup.mp4 (186.2 MB)
• 1. Anaconda Environment Setup.srt (20.1 KB)
• 2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 (43.9 MB)
• 2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt (14.5 KB)

• [Tutorialsplanet.NET].url (0.1 KB)