Udemy - Advanced AI: Deep Reinforcement Learning in Python

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[Tutorialsplanet.NET] Udemy - Advanced AI Deep Reinforcement Learning in Python 1. Introduction and Logistics
  • 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)
10. Extra Help With Python Coding for Beginners (FAQ by Student Request)
  • 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)
11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)
  • 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)
12. Appendix FAQ Finale
  • 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)
2. The Basics of Reinforcement Learning
  • 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)
3. OpenAI Gym and Basic Reinforcement Learning Techniques
  • 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)
4. TD Lambda
  • 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)
5. Policy Gradients
  • 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 CartPo

Description

Udemy - Advanced AI: Deep Reinforcement Learning in Python

This course is all about the application of deep learning and neural networks to reinforcement learning.

If you’ve taken my first reinforcement learning class, then you know that reinforcement learning is on the bleeding edge of what we can do with AI.

Specifically, the combination of deep learning with reinforcement learning has led to AlphaGo beating a world champion in the strategy game Go, it has led to self-driving cars, and it has led to machines that can play video games at a superhuman level.

Reinforcement learning has been around since the 70s but none of this has been possible until now.
For more Udemy Courses: https://tutorialsplanet.net



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Udemy - Advanced AI: Deep Reinforcement Learning in Python

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2.8 GB
seeders:8
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Udemy - Advanced AI: Deep Reinforcement Learning in Python

Torrent hash: A1C3E8FEB6DD4AAAC0089AFE05E2622FBFC7AFE0