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Advanced AI Deep Reinforcement Learning in Python
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Name:Advanced AI Deep Reinforcement Learning in Python
Infohash: 650162511775FAFF90D20973FE23B8FFF1B06390
Total Size: 2.93 GB
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Last Updated: 2025-12-30 23:13:13 (Update Now)
Torrent added: 2021-03-07 05:30:14
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[TutsNode.com] - Advanced AI Deep Reinforcement Learning in Python (Size: 2.93 GB) (Files: 239)
[TutsNode.com] - Advanced AI Deep Reinforcement Learning in Python
6. Deep Q-Learning
7. Deep Q-Learning in Tensorflow for Breakout.mp4
7. Deep Q-Learning in Tensorflow for Breakout.srt
8. Deep Q-Learning in Theano for Breakout.srt
8. Deep Q-Learning in Theano for Breakout.mp4
2. Deep Q-Learning Techniques.srt
6. Pseudocode and Replay Memory.srt
5. Additional Implementation Details for Atari.srt
10. Deep Q-Learning Section Summary.srt
3. Deep Q-Learning in Tensorflow for CartPole.srt
9. Partially Observable MDPs.srt
4. Deep Q-Learning in Theano for CartPole.srt
1. Deep Q-Learning Intro.srt
6. Pseudocode and Replay Memory.mp4
3. Deep Q-Learning in Tensorflow for CartPole.mp4
2. Deep Q-Learning Techniques.mp4
4. Deep Q-Learning in Theano for CartPole.mp4
10. Deep Q-Learning Section Summary.mp4
5. Additional Implementation Details for Atari.mp4
9. Partially Observable MDPs.mp4
1. Deep Q-Learning Intro.mp4
11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt
4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt
3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt
1. How to Succeed in this Course (Long Version).srt
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4
4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4
3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4
1. How to Succeed in this Course (Long Version).mp4
2. The Basics of Reinforcement Learning
2. Elements of a Reinforcement Learning Problem.srt
11. Q-Learning.srt
9. Solving the Bellman Equation with Reinforcement Learning (pt 2).srt
4. Markov Decision Processes (MDPs).srt
6. Value Functions and the Bellman Equation.srt
8. Solving the Bellman Equation with Reinforcement Learning (pt 1).srt
3. States, Actions, Rewards, Policies.srt
7. What does it mean to “learnâ€.srt
1. Reinforcement Learning Section Introduction.srt
10. Epsilon-Greedy.srt
12. How to Learn Reinforcement Learning.srt
5. The Return.srt
13. Suggestion Box.srt
2. Elements of a Reinforcement Learning Problem.mp4
11. Q-Learning.mp4
9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4
4. Markov Decision Processes (MDPs).mp4
6. Value Functions and the Bellman Equation.mp4
3. States, Actions, Rewards, Policies.mp4
8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4
10. Epsilon-Greedy.mp4
1. Reinforcement Learning Section Introduction.mp4
12. How to Learn Reinforcement Learning.mp4
7. What does it mean to “learnâ€.mp4
5. The Return.mp4
13. Suggestion Box.mp4
1. Introduction and Logistics
2.1 Github Link.html
3. Anyone Can Succeed in this Course.srt
1. Introduction and Outline.srt
2. Where to get the Code.srt
4. Tensorflow or Theano - Your Choice!.srt
3. Anyone Can Succeed in this Course.mp4
1. Introduction and Outline.mp4
2. Where to get the Code.mp4
4. Tensorflow or Theano - Your Choice!.mp4
10. Extra Help With Python Coding for Beginners (FAQ by Student Request)
1. How to Code by Yourself (part 1).srt
3. Proof that using Jupyter Notebook is the same as not using it.srt
2. How to Code by Yourself (part 2).srt
5. Is Theano Dead.srt
4. Python 2 vs Python 3.srt
3. Proof that using Jupyter Notebook is the same as not using it.mp4
1. How to Code by Yourself (part 1).mp4
5. Is Theano Dead.mp4
2. How to Code by Yourself (part 2).mp4
4. Python 2 vs Python 3.mp4
7. A3C
5. A3C - Code pt 4.srt
1. A3C - Theory and Outline.srt
4. A3C - Code pt 3.srt
3. A3C - Code pt 2.srt
2. A3C - Code pt 1 (Warmup).srt
7. Course Summary.srt
6. A3C - Section Summary.srt
5. A3C - Code pt 4.mp4
4. A3C - Code pt 3.mp4
1. A3C - Theory and Outline.mp4
3. A3C - Code pt 2.mp4
2. A3C - Code pt 1 (Warmup).mp4
7. Course Summary.mp4
6. A3C - Section Summary.mp4
9. Setting Up Your Environment (FAQ by Student Request)
1. Windows-Focused Environment Setup 2018.srt
2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt
1. Windows-Focused Environment Setup 2018.mp4
2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
5. Policy Gradients
1. Policy Gradient Methods.srt
7. Mountain Car Continuous Tensorflow.srt
6. Mountain Car Continuous Theano.srt
2. Policy Gradient in TensorFlow for CartPole.srt
9. Mountain Car Continuous Theano (v2).srt
8. Mountain Car Continuous Tensorflow (v2).srt
4. Continuous Action Spaces.srt
3. Policy Gradient in Theano for CartPole.srt
5. Mountain Car Continuous Specifics.srt
10. Policy Gradient Section Summary.srt
9. Mountain Car Continuous Theano (v2).mp4
7. Mountain Car Continuous Tensorflow.mp4
6. Mountain Car Continuous Theano.mp4
8. Mountain Car Continuous Tensorflow (v2).mp4
2. Policy Gradient in TensorFlow for CartPole.mp4
1. Policy Gradient Methods.mp4
3. Policy Gradient in Theano for CartPole.mp4
4. Continuous Action Spaces.mp4
5. Mountain Car Continuous Specifics.mp4
10. Policy Gradient Section Summary.mp4
3. OpenAI Gym and Basic Reinforcement Learning Techniques
6. RBF Neural Networks.srt
5. CartPole with Bins (Code).srt
3. Saving a Video.srt
1. OpenAI Gym Tutorial.srt
8. RBF Networks with CartPole (Theory).srt
2. Random Search.srt
7. RBF Networks with Mountain Car (Code).srt
11. Tensorflow Warmup.srt
4. CartPole with Bins (Theory).srt
12. Plugging in a Neural Network.srt
13. OpenAI Gym Section Summary.srt
9. RBF Networks with CartPole (Code).srt
10. Theano Warmup.srt
6. RBF Neural Networks.mp4
5. CartPole with Bins (Code).mp4
7. RBF Networks with Mountain Car (Code).mp4
2. Random Search.mp4
9. RBF Networks with CartPole (Code).mp4
1. OpenAI Gym Tutorial.mp4
4. CartPole with Bins (Theory).mp4
12. Plugging in a Neural Network.mp4
10. Theano Warmup.mp4
13. OpenAI Gym Section Summary.mp4
11. Tensorflow Warmup.mp4
3. Saving a Video.mp4
8. RBF Networks with CartPole (Theory).mp4
4. TD Lambda
2. N-Step in Code.srt
3. TD Lambda.srt
5. TD Lambda Summary.srt
1. N-Step Methods.srt
4. TD Lambda in Code.srt
1. N-Step Methods.mp4
3. TD Lambda.mp4
2. N-Step in Code.mp4
4. TD Lambda in Code.mp4
5. TD Lambda Summary.mp4
12. Appendix FAQ Finale
2. BONUS Where to get Udemy coupons and FREE deep learning material.srt
1. What is the Appendix.srt
2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4
1. What is the Appendix.mp4
8. Theano and Tensorflow Basics Review
1. (Review) Theano Basics.srt
4. (Review) Tensorflow Neural Network in Code.srt
3. (Review) Tensorflow Basics.srt
2. (Review) Theano Neural Network in Code.srt
4. (Review) Tensorflow Neural Network in Code.mp4
1. (Review) Theano Basics.mp4
2. (Review) Theano Neural Network in Code.mp4
3. (Review) Tensorflow Basics.mp4
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