[FreeCourseLab.com] Udemy - Advanced AI Deep Reinforcement Learning in Python
    
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                    - 9. Appendix/3. Windows-Focused Environment Setup 2018.mp4  186.2 MB
 
                
                    - 7. A3C/5. A3C - Code pt 4.mp4  184.4 MB
 
                
                    - 8. Theano and Tensorflow Basics Review/4. (Review) Tensorflow Neural Network in Code.mp4  97.3 MB
 
                
                    - 8. Theano and Tensorflow Basics Review/1. (Review) Theano Basics.mp4  93.4 MB
 
                
                    - 8. Theano and Tensorflow Basics Review/2. (Review) Theano Neural Network in Code.mp4  87.0 MB
 
                
                    - 7. A3C/4. A3C - Code pt 3.mp4  84.5 MB
 
                
                    - 8. Theano and Tensorflow Basics Review/3. (Review) Tensorflow Basics.mp4  81.4 MB
 
                
                    - 9. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.mp4  78.3 MB
 
                
                    - 7. A3C/1. A3C - Theory and Outline.mp4  71.8 MB
 
                
                    - 7. A3C/3. A3C - Code pt 2.mp4  57.6 MB
 
                
                    - 7. A3C/2. A3C - Code pt 1 (Warmup).mp4  50.1 MB
 
                
                    - 9. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4  43.9 MB
 
                
                    - 9. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4  39.0 MB
 
                
                    - 9. Appendix/13. What order should I take your courses in (part 2).mp4  37.6 MB
 
                
                    - 9. Appendix/12. What order should I take your courses in (part 1).mp4  29.3 MB
 
                
                    - 9. Appendix/5. How to Code by Yourself (part 1).mp4  24.5 MB
 
                
                    - 5. Policy Gradients/9. Mountain Car Continuous Theano (v2).mp4  22.2 MB
 
                
                    - 5. Policy Gradients/7. Mountain Car Continuous Tensorflow.mp4  20.1 MB
 
                
                    - 6. Deep Q-Learning/7. Deep Q-Learning in Theano for Breakout.mp4  20.0 MB
 
                
                    - 5. Policy Gradients/6. Mountain Car Continuous Theano.mp4  19.1 MB
 
                
                    - 1. Introduction and Logistics/4. Tensorflow or Theano - Your Choice!.mp4  18.9 MB
 
                
                    - 5. Policy Gradients/8. Mountain Car Continuous Tensorflow (v2).mp4  18.8 MB
 
                
                    - 9. Appendix/7. How to Succeed in this Course (Long Version).mp4  18.3 MB
 
                
                    - 5. Policy Gradients/2. Policy Gradient in TensorFlow for CartPole.mp4  18.0 MB
 
                
                    - 5. Policy Gradients/1. Policy Gradient Methods.mp4  18.0 MB
 
                
                    - 9. Appendix/11. Is Theano Dead.mp4  17.8 MB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/6. RBF Neural Networks.mp4  16.5 MB
 
                
                    - 1. Introduction and Logistics/1. Introduction and Outline.mp4  15.8 MB
 
                
                    - 6. Deep Q-Learning/6. Deep Q-Learning in Tensorflow for Breakout.mp4  15.8 MB
 
                
                    - 6. Deep Q-Learning/3. Deep Q-Learning in Tensorflow for CartPole.mp4  15.0 MB
 
                
                    - 9. Appendix/6. How to Code by Yourself (part 2).mp4  14.8 MB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/5. CartPole with Bins (Code).mp4  14.7 MB
 
                
                    - 6. Deep Q-Learning/2. Deep Q-Learning Techniques.mp4  14.5 MB
 
                
                    - 6. Deep Q-Learning/4. Deep Q-Learning in Theano for CartPole.mp4  13.8 MB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/7. RBF Networks with Mountain Car (Code).mp4  13.7 MB
 
                
                    - 5. Policy Gradients/3. Policy Gradient in Theano for CartPole.mp4  13.4 MB
 
                
                    - 2. Background Review/2. Review of Markov Decision Processes.mp4  12.3 MB
 
                
                    - 4. TD Lambda/3. TD Lambda.mp4  11.8 MB
 
                
                    - 2. Background Review/7. Review of Deep Learning.mp4  11.0 MB
 
                
                    - 6. Deep Q-Learning/9. Deep Q-Learning Section Summary.mp4  10.4 MB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/2. Random Search.mp4  10.3 MB
 
                
                    - 4. TD Lambda/2. N-Step in Code.mp4  9.5 MB
 
                
                    - 7. A3C/7. Course Summary.mp4  9.5 MB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/9. RBF Networks with CartPole (Code).mp4  8.9 MB
 
                
                    - 7. A3C/6. A3C - Section Summary.mp4  8.9 MB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/1. OpenAI Gym Tutorial.mp4  8.7 MB
 
                
                    - 6. Deep Q-Learning/5. Additional Implementation Details for Atari.mp4  8.5 MB
 
                
                    - 9. Appendix/10. Python 2 vs Python 3.mp4  7.8 MB
 
                
                    - 4. TD Lambda/4. TD Lambda in Code.mp4  7.6 MB
 
                
                    - 6. Deep Q-Learning/8. Partially Observable MDPs.mp4  7.6 MB
 
                
                    - 2. Background Review/5. Review of Temporal Difference Learning.mp4  7.2 MB
 
                
                    - 5. Policy Gradients/4. Continuous Action Spaces.mp4  6.6 MB
 
                
                    - 2. Background Review/3. Review of Dynamic Programming.mp4  6.5 MB
 
                
                    - 5. Policy Gradients/5. Mountain Car Continuous Specifics.mp4  6.5 MB
 
                
                    - 2. Background Review/4. Review of Monte Carlo Methods.mp4  6.2 MB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/4. CartPole with Bins (Theory).mp4  6.0 MB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/12. Plugging in a Neural Network.mp4  5.9 MB
 
                
                    - 6. Deep Q-Learning/1. Deep Q-Learning Intro.mp4  5.9 MB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/10. Theano Warmup.mp4  5.8 MB
 
                
                    - 9. Appendix/1. What is the Appendix.mp4  5.5 MB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/13. OpenAI Gym Section Summary.mp4  5.3 MB
 
                
                    - 1. Introduction and Logistics/2. Where to get the Code.mp4  5.2 MB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/11. Tensorflow Warmup.mp4  5.1 MB
 
                
                    - 4. TD Lambda/1. N-Step Methods.mp4  5.0 MB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/3. Saving a Video.mp4  4.5 MB
 
                
                    - 2. Background Review/1. Review Intro.mp4  4.2 MB
 
                
                    - 9. Appendix/2. Where to get Udemy coupons and FREE deep learning material.mp4  4.0 MB
 
                
                    - 2. Background Review/6. Review of Approximation Methods for Reinforcement Learning.mp4  3.7 MB
 
                
                    - 4. TD Lambda/5. TD Lambda Summary.mp4  3.6 MB
 
                
                    - 5. Policy Gradients/10. Policy Gradient Section Summary.mp4  3.3 MB
 
                
                    - 1. Introduction and Logistics/3. How to Succeed in this Course.mp4  3.3 MB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/8. RBF Networks with CartPole (Theory).mp4  3.1 MB
 
                
                    - 9. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt  27.8 KB
 
                
                    - 9. Appendix/13. What order should I take your courses in (part 2).vtt  20.2 KB
 
                
                    - 9. Appendix/5. How to Code by Yourself (part 1).vtt  19.8 KB
 
                
                    - 7. A3C/5. A3C - Code pt 4.vtt  18.6 KB
 
                
                    - 7. A3C/1. A3C - Theory and Outline.vtt  17.9 KB
 
                
                    - 9. Appendix/3. Windows-Focused Environment Setup 2018.vtt  17.4 KB
 
                
                    - 9. Appendix/12. What order should I take your courses in (part 1).vtt  14.1 KB
 
                
                    - 5. Policy Gradients/1. Policy Gradient Methods.vtt  13.0 KB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/6. RBF Neural Networks.vtt  12.8 KB
 
                
                    - 9. Appendix/7. How to Succeed in this Course (Long Version).vtt  12.8 KB
 
                
                    - 1. Introduction and Logistics/1. Introduction and Outline.vtt  12.8 KB
 
                
                    - 9. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt  12.4 KB
 
                
                    - 9. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.vtt  12.2 KB
 
                
                    - 9. Appendix/6. How to Code by Yourself (part 2).vtt  11.6 KB
 
                
                    - 9. Appendix/11. Is Theano Dead.vtt  11.3 KB
 
                
                    - 6. Deep Q-Learning/2. Deep Q-Learning Techniques.vtt  10.8 KB
 
                
                    - 5. Policy Gradients/7. Mountain Car Continuous Tensorflow.vtt  9.0 KB
 
                
                    - 2. Background Review/2. Review of Markov Decision Processes.vtt  8.9 KB
 
                
                    - 5. Policy Gradients/6. Mountain Car Continuous Theano.vtt  8.6 KB
 
                
                    - 4. TD Lambda/3. TD Lambda.vtt  8.2 KB
 
                
                    - 2. Background Review/7. Review of Deep Learning.vtt  8.2 KB
 
                
                    - 7. A3C/4. A3C - Code pt 3.vtt  8.0 KB
 
                
                    - 5. Policy Gradients/2. Policy Gradient in TensorFlow for CartPole.vtt  7.7 KB
 
                
                    - 5. Policy Gradients/9. Mountain Car Continuous Theano (v2).vtt  7.4 KB
 
                
                    - 7. A3C/3. A3C - Code pt 2.vtt  7.3 KB
 
                
                    - 6. Deep Q-Learning/7. Deep Q-Learning in Theano for Breakout.vtt  7.1 KB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/5. CartPole with Bins (Code).vtt  7.0 KB
 
                
                    - 7. A3C/2. A3C - Code pt 1 (Warmup).vtt  6.8 KB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/1. OpenAI Gym Tutorial.vtt  6.8 KB
 
                
                    - 8. Theano and Tensorflow Basics Review/1. (Review) Theano Basics.vtt  6.3 KB
 
                
                    - 5. Policy Gradients/8. Mountain Car Continuous Tensorflow (v2).vtt  6.2 KB
 
                
                    - 6. Deep Q-Learning/5. Additional Implementation Details for Atari.vtt  6.2 KB
 
                
                    - 6. Deep Q-Learning/6. Deep Q-Learning in Tensorflow for Breakout.vtt  6.1 KB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/2. Random Search.vtt  6.0 KB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/7. RBF Networks with Mountain Car (Code).vtt  5.7 KB
 
                
                    - 9. Appendix/10. Python 2 vs Python 3.vtt  5.4 KB
 
                
                    - 7. A3C/7. Course Summary.vtt  5.3 KB
 
                
                    - 6. Deep Q-Learning/9. Deep Q-Learning Section Summary.vtt  5.3 KB
 
                
                    - 2. Background Review/5. Review of Temporal Difference Learning.vtt  5.2 KB
 
                
                    - 6. Deep Q-Learning/3. Deep Q-Learning in Tensorflow for CartPole.vtt  5.1 KB
 
                
                    - 6. Deep Q-Learning/8. Partially Observable MDPs.vtt  5.1 KB
 
                
                    - 8. Theano and Tensorflow Basics Review/3. (Review) Tensorflow Basics.vtt  5.1 KB
 
                
                    - 6. Deep Q-Learning/4. Deep Q-Learning in Theano for CartPole.vtt  4.8 KB
 
                
                    - 8. Theano and Tensorflow Basics Review/4. (Review) Tensorflow Neural Network in Code.vtt  4.8 KB
 
                
                    - 1. Introduction and Logistics/4. Tensorflow or Theano - Your Choice!.vtt  4.8 KB
 
                
                    - 2. Background Review/3. Review of Dynamic Programming.vtt  4.7 KB
 
                
                    - 5. Policy Gradients/4. Continuous Action Spaces.vtt  4.7 KB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/4. CartPole with Bins (Theory).vtt  4.6 KB
 
                
                    - 5. Policy Gradients/5. Mountain Car Continuous Specifics.vtt  4.4 KB
 
                
                    - 2. Background Review/4. Review of Monte Carlo Methods.vtt  4.4 KB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/12. Plugging in a Neural Network.vtt  4.3 KB
 
                
                    - 6. Deep Q-Learning/1. Deep Q-Learning Intro.vtt  4.2 KB
 
                
                    - 1. Introduction and Logistics/2. Where to get the Code.vtt  4.1 KB
 
                
                    - 5. Policy Gradients/3. Policy Gradient in Theano for CartPole.vtt  4.0 KB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/13. OpenAI Gym Section Summary.vtt  3.7 KB
 
                
                    - 4. TD Lambda/2. N-Step in Code.vtt  3.7 KB
 
                
                    - 1. Introduction and Logistics/3. How to Succeed in this Course.vtt  3.5 KB
 
                
                    - 4. TD Lambda/1. N-Step Methods.vtt  3.4 KB
 
                
                    - 8. Theano and Tensorflow Basics Review/2. (Review) Theano Neural Network in Code.vtt  3.3 KB
 
                
                    - 9. Appendix/1. What is the Appendix.vtt  3.3 KB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/9. RBF Networks with CartPole (Code).vtt  3.2 KB
 
                
                    - 2. Background Review/1. Review Intro.vtt  3.1 KB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/10. Theano Warmup.vtt  3.1 KB
 
                
                    - 9. Appendix/2. Where to get Udemy coupons and FREE deep learning material.vtt  3.0 KB
 
                
                    - 4. TD Lambda/4. TD Lambda in Code.vtt  2.9 KB
 
                
                    - 4. TD Lambda/5. TD Lambda Summary.vtt  2.6 KB
 
                
                    - 2. Background Review/6. Review of Approximation Methods for Reinforcement Learning.vtt  2.5 KB
 
                
                    - 7. A3C/6. A3C - Section Summary.vtt  2.4 KB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/11. Tensorflow Warmup.vtt  2.2 KB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/8. RBF Networks with CartPole (Theory).vtt  2.2 KB
 
                
                    - 3. OpenAI Gym and Basic Reinforcement Learning Techniques/3. Saving a Video.vtt  2.1 KB
 
                
                    - 5. Policy Gradients/10. Policy Gradient Section Summary.vtt  1.7 KB
 
                
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