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Category:
Language:
English
Total Size:
2.8 GB
Info Hash:
A1C3E8FEB6DD4AAAC0089AFE05E2622FBFC7AFE0
Added By:
Added:
Oct. 24, 2023, 5:18 p.m.
Stats:
|
(Last updated: May 19, 2025, 2:51 a.m.)
| File | Size |
|---|---|
| 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 | 120 bytes |
| 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 | 128 bytes |
| 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 | 128 bytes |
| 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 bytes |
| 2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt | 0 bytes |
| 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 | 128 bytes |
Name
DL
Uploader
Size
S/L
Added
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2.7 GB
[11
/
3]
2025-01-13
| Uploaded by FreeCourseWeb | Size 2.7 GB | Health [ 11 /3 ] | Added 2025-01-13 |
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3.8 GB
[3
/
17]
2024-10-24
| Uploaded by FreeCourseWeb | Size 3.8 GB | Health [ 3 /17 ] | Added 2024-10-24 |
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1.7 GB
[20
/
5]
2024-02-29
| Uploaded by FreeCourseWeb | Size 1.7 GB | Health [ 20 /5 ] | Added 2024-02-29 |
-
354.4 MB
[19
/
10]
2024-02-15
| Uploaded by FreeCourseWeb | Size 354.4 MB | Health [ 19 /10 ] | Added 2024-02-15 |
NOTE
SOURCE: Udemy Advanced AI Deep Reinforcement Learning in Python
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