| 1. Approximation Intro.mp4 | 6.5 MB | ||
| 1. Approximation Intro.srt | 8 KB | ||
| 1. Gridworld.mp4 | 3.4 MB | ||
| 1. Gridworld.srt | 4 KB | ||
| 1. Intro to Dynamic Programming and Iterative Policy Evaluation.mp4 | 4.8 MB | ||
| 1. Intro to Dynamic Programming and Iterative Policy Evaluation.srt | 5.4 KB | ||
| 1. Introduction.mp4 | 34.2 MB | ||
| 1. Introduction.srt | 4.2 KB | ||
| 1. Monte Carlo Intro.mp4 | 5 MB | ||
| 1. Monte Carlo Intro.srt | 6 KB | ||
| 1. Naive Solution to Tic-Tac-Toe.mp4 | 6.1 MB | ||
| 1. Naive Solution to Tic-Tac-Toe.srt | 7.2 KB | ||
| 1. Problem Setup and The Explore-Exploit Dilemma.mp4 | 6.5 MB | ||
| 1. Problem Setup and The Explore-Exploit Dilemma.srt | 7.8 KB | ||
| 1. Stock Trading Project Section Introduction.mp4 | 26.8 MB | ||
| 1. Stock Trading Project Section Introduction.srt | 6.8 KB | ||
| 1. Temporal Difference Intro.mp4 | 2.7 MB | ||
| 1. Temporal Difference Intro.srt | 3.3 KB | ||
| 1. What is Reinforcement Learning.mp4 | 54.6 MB | ||
| 1. What is Reinforcement Learning.srt | 10.9 KB | ||
| 1. What is the Appendix.mp4 | 5.5 MB | ||
| 1. What is the Appendix.srt | 3.7 KB | ||
| 10. Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.mp4 | 10.6 MB | ||
| 10. Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.srt | 6.1 KB | ||
| 10. Tic Tac Toe Code Main Loop and Demo.mp4 | 9.4 MB | ||
| 10. Tic Tac Toe Code Main Loop and Demo.srt | 9.2 KB | ||
| 10. Value Iteration in Code.mp4 | 4.9 MB | ||
| 10. Value Iteration in Code.srt | 3.3 KB | ||
| 10. What order should I take your courses in (part 1).mp4 | 29.3 MB | ||
| 10. What order should I take your courses in (part 1).srt | 16 KB | ||
| 11. Dynamic Programming Summary.mp4 | 8.3 MB | ||
| 11. Dynamic Programming Summary.srt | 9.4 KB | ||
| 11. Nonstationary Bandits.mp4 | 7.5 MB | ||
| 11. Nonstationary Bandits.srt | 7.8 KB | ||
| 11. Tic Tac Toe Summary.mp4 | 8.3 MB | ||
| 11. Tic Tac Toe Summary.srt | 10.2 KB | ||
| 11. What order should I take your courses in (part 2).mp4 | 37.6 MB | ||
| 11. What order should I take your courses in (part 2).srt | 23 KB | ||
| 12. BONUS Where to get discount coupons and FREE deep learning material.mp4 | 37.8 MB | ||
| 12. BONUS Where to get discount coupons and FREE deep learning material.srt | 7.9 KB | ||
| 12. Bandit Summary, Real Data, and Online Learning.mp4 | 33.9 MB | ||
| 12. Bandit Summary, Real Data, and Online Learning.srt | 9.1 KB | ||
| 12. Tic Tac Toe Exercise.mp4 | 19.8 MB | ||
| 12. Tic Tac Toe Exercise.srt | 4.6 KB | ||
| 2. Applications of the Explore-Exploit Dilemma.mp4 | 51.2 MB | ||
| 2. Applications of the Explore-Exploit Dilemma.srt | 10.9 KB | ||
| 2. Components of a Reinforcement Learning System.mp4 | 12.7 MB | ||
| 2. Components of a Reinforcement Learning System.srt | 14.8 KB | ||
| 2. Data and Environment.mp4 | 52 MB | ||
| 2. Data and Environment.srt | 15.7 KB | ||
| 2. Gridworld in Code.mp4 | 11.5 MB | ||
| 2. Gridworld in Code.srt | 11 KB | ||
| 2. Linear Models for Reinforcement Learning.mp4 | 6.5 MB | ||
| 2. Linear Models for Reinforcement Learning.srt | 7.4 KB | ||
| 2. Monte Carlo Policy Evaluation.mp4 | 8.8 MB | ||
| 2. Monte Carlo Policy Evaluation.srt | 10.8 KB | ||
| 2. On Unusual or Unexpected Strategies of RL.mp4 | 37.1 MB | ||
| 2. On Unusual or Unexpected Strategies of RL.srt | 7.9 KB | ||
| 2. TD(0) Prediction.mp4 | 5.8 MB | ||
| 2. TD(0) Prediction.srt | 6.4 KB | ||
| 2. The Markov Property.mp4 | 7.2 MB | ||
| 2. The Markov Property.srt | 8.4 KB | ||
| 2. Where to get the Code.mp4 | 4.4 MB | ||
| 2. Where to get the Code.srt | 5.4 KB | ||
| 2. Windows-Focused Environment Setup 2018.mp4 | 186.4 MB | ||
| 2. Windows-Focused Environment Setup 2018.srt | 20.1 KB | ||
| 3. Defining Some Terms.mp4 | 42.3 MB | ||
| 3. Defining Some Terms.srt | 9.1 KB | ||
| 3. Defining and Formalizing the MDP.mp4 | 6.6 MB | ||
| 3. Defining and Formalizing the MDP.srt | 7.9 KB | ||
| 3. Designing Your RL Program.mp4 | 22.3 MB | ||
| 3. Designing Your RL Program.srt | 6.6 KB | ||
| 3. Epsilon-Greedy.mp4 | 2.8 MB | ||
| 3. Epsilon-Greedy.srt | 3.2 KB | ||
| 3. Features.mp4 | 6.3 MB | ||
| 3. Features.srt | 6.9 KB | ||
| 3. How to Model Q for Q-Learning.mp4 | 44.9 MB | ||
| 3. How to Model Q for Q-Learning.srt | 12 KB | ||
| 3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 | 43.9 MB | ||
| 3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt | 18.3 KB | ||
| 3. Monte Carlo Policy Evaluation in Code.mp4 | 7.9 MB | ||
| 3. Monte Carlo Policy Evaluation in Code.srt | 6.1 KB | ||
| 3. Notes on Assigning Rewards.mp4 | 4.2 MB | ||
| 3. Notes on Assigning Rewards.srt | 4.9 KB | ||
| 3. Strategy for Passing the Course.mp4 | 9.5 MB | ||
| 3. Strategy for Passing the Course.srt | 11.8 KB | ||
| 3. TD(0) Prediction in Code.mp4 | 5.3 MB | ||
| 3. TD(0) Prediction in Code.srt | 4 KB | ||
| 4. Course Outline.mp4 | 31 MB | ||
| 4. Course Outline.srt | 6.8 KB | ||
| 4. Design of the Program.mp4 | 23.3 MB | ||
| 4. Design of the Program.srt | 8.5 KB | ||
| 4. Future Rewards.mp4 | 5.2 MB | ||
| 4. Future Rewards.srt | 6 KB | ||
| 4. How to Code by Yourself (part 1).mp4 | 24.5 MB | ||
| 4. How to Code by Yourself (part 1).srt | 30.2 KB | ||
| 4. Iterative Policy Evaluation in Code.mp4 | 12.1 MB | ||
| 4. Iterative Policy Evaluation in Code.srt | 10.2 KB | ||
| 4. Monte Carlo Prediction with Approximation.mp4 | 2.8 MB | ||
| 4. Monte Carlo Prediction with Approximation.srt | 2.3 KB | ||
| 4. Policy Evaluation in Windy Gridworld.mp4 | 7.8 MB | ||
| 4. Policy Evaluation in Windy Gridworld.srt | 5.3 KB | ||
| 4. SARSA.mp4 | 8.2 MB | ||
| 4. SARSA.srt | 9.7 KB | ||
| 4. The Value Function and Your First Reinforcement Learning Algorithm.mp4 | 103.7 MB | ||
| 4. The Value Function and Your First Reinforcement Learning Algorithm.srt | 22.8 KB | ||
| 4. Updating a Sample Mean.mp4 | 2.2 MB | ||
| 4. Updating a Sample Mean.srt | 2.2 KB | ||
| 5. Code pt 1.mp4 | 49.7 MB | ||
| 5. Code pt 1.srt | 9.6 KB | ||
| 5. Designing Your Bandit Program.mp4 | 24.5 MB | ||
| 5. Designing Your Bandit Program.srt | 5.6 KB | ||
| 5. How to Code by Yourself (part 2).mp4 | 14.8 MB | ||
| 5. How to Code by Yourself (part 2).srt | 18.4 KB | ||
| 5. Monte Carlo Control.mp4 | 9.3 MB | ||
| 5. Monte Carlo Control.srt | 10.2 KB | ||
| 5. Monte Carlo Prediction with Approximation in Code.mp4 | 6.6 MB | ||
| 5. Monte Carlo Prediction with Approximation in Code.srt | 4 KB | ||
| 5. Policy Improvement.mp4 | 4.5 MB | ||
| 5. Policy Improvement.srt | 5.2 KB | ||
| 5. SARSA in Code.mp4 | 8.8 MB | ||
| 5. SARSA in Code.srt | 5.5 KB | ||
| 5. Tic Tac Toe Code Outline.mp4 | 5 MB | ||
| 5. Tic Tac Toe Code Outline.srt | 6.4 KB | ||
| 5. Value Function Introduction.mp4 | 19.7 MB | ||
| 5. Value Function Introduction.srt | 15.6 KB | ||
| 6. Code pt 2.mp4 | 65.3 MB | ||
| 6. Code pt 2.srt | 11.8 KB | ||
| 6. Comparing Different Epsilons.mp4 | 8 MB | ||
| 6. Comparing Different Epsilons.srt | 5.3 KB | ||
| 6. How to Succeed in this Course (Long Version).mp4 | 18.3 MB | ||
| 6. How to Succeed in this Course (Long Version).srt | 14.5 KB | ||
| 6. Monte Carlo Control in Code.mp4 | 10.2 MB | ||
| 6. Monte Carlo Control in Code.srt | 5.8 KB | ||
| 6. Policy Iteration.mp4 | 3.1 MB | ||
| 6. Policy Iteration.srt | 3.5 KB | ||
| 6. Q Learning.mp4 | 4.8 MB | ||
| 6. Q Learning.srt | 5.8 KB | ||
| 6. TD(0) Semi-Gradient Prediction.mp4 | 8.4 MB | ||
| 6. TD(0) Semi-Gradient Prediction.srt | 6.4 KB | ||
| 6. Tic Tac Toe Code Representing States.mp4 | 4.4 MB | ||
| 6. Tic Tac Toe Code Representing States.srt | 4.9 KB | ||
| 6. Value Functions.mp4 | 8.3 MB | ||
| 6. Value Functions.srt | 11.8 KB | ||
| 7. Bellman Examples.mp4 | 87.1 MB | ||
| 7. Bellman Examples.srt | 27.7 KB | ||
| 7. Code pt 3.mp4 | 33.7 MB | ||
| 7. Code pt 3.srt | 5.4 KB | ||
| 7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 | 39 MB | ||
| 7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt | 31.8 KB | ||
| 7. Monte Carlo Control without Exploring Starts.mp4 | 4.6 MB | ||
| 7. Monte Carlo Control without Exploring Starts.srt | 5.5 KB | ||
| 7. Optimistic Initial Values.mp4 | 15.8 MB | ||
| 7. Optimistic Initial Values.srt | 3.1 KB | ||
| 7. Policy Iteration in Code.mp4 | 7.6 MB | ||
| 7. Policy Iteration in Code.srt | 6.1 KB | ||
| 7. Q Learning in Code.mp4 | 5.4 MB | ||
| 7. Q Learning in Code.srt | 3.5 KB | ||
| 7. Semi-Gradient SARSA.mp4 | 4.7 MB | ||
| 7. Semi-Gradient SARSA.srt | 5.5 KB | ||
| 7. Tic Tac Toe Code Enumerating States Recursively.mp4 | 9.8 MB | ||
| 7. Tic Tac Toe Code Enumerating States Recursively.srt | 11.3 KB | ||
| 8. Code pt 4.mp4 | 49.1 MB | ||
| 8. Code pt 4.srt | 8 KB | ||
| 8. Monte Carlo Control without Exploring Starts in Code.mp4 | 8.1 MB | ||
| 8. Monte Carlo Control without Exploring Starts in Code.srt | 3.6 KB | ||
| 8. Optimal Policy and Optimal Value Function.mp4 | 3.2 MB | ||
| 8. Optimal Policy and Optimal Value Function.srt | 5 KB | ||
| 8. Policy Iteration in Windy Gridworld.mp4 | 9.1 MB | ||
| 8. Policy Iteration in Windy Gridworld.srt | 8.2 KB | ||
| 8. Proof that using Jupyter Notebook is the same as not using it.mp4 | 78.3 MB | ||
| 8. Proof that using Jupyter Notebook is the same as not using it.srt | 14.1 KB | ||
| 8. Semi-Gradient SARSA in Code.mp4 | 10.6 MB | ||
| 8. Semi-Gradient SARSA in Code.srt | 5.4 KB | ||
| 8. TD Summary.mp4 | 3.9 MB | ||
| 8. TD Summary.srt | 4.7 KB | ||
| 8. Tic Tac Toe Code The Environment.mp4 | 10 MB | ||
| 8. Tic Tac Toe Code The Environment.srt | 12 KB | ||
| 8. UCB1.mp4 | 8.2 MB | ||
| 8. UCB1.srt | 8.1 KB | ||
| 9. Bayesian Thompson Sampling.mp4 | 51.8 MB | ||
| 9. Bayesian Thompson Sampling.srt | 11.8 KB | ||
| 9. Course Summary and Next Steps.mp4 | 13.2 MB | ||
| 9. Course Summary and Next Steps.srt | 16 KB | ||
| 9. MDP Summary.mp4 | 5.7 MB | ||
| 9. MDP Summary.srt | 2 KB | ||
| 9. Monte Carlo Summary.mp4 | 5.7 MB | ||
| 9. Monte Carlo Summary.srt | 7.1 KB | ||
| 9. Python 2 vs Python 3.mp4 | 7.8 MB | ||
| 9. Python 2 vs Python 3.srt | 6.1 KB | ||
| 9. Stock Trading Project Discussion.mp4 | 15.8 MB | ||
| 9. Stock Trading Project Discussion.srt | 4.3 KB | ||
| 9. Tic Tac Toe Code The Agent.mp4 | 9 MB | ||
| 9. Tic Tac Toe Code The Agent.srt | 10.9 KB | ||
| 9. Value Iteration.mp4 | 6.2 MB | ||
| 9. Value Iteration.srt | 7 KB | ||
| [CourseClub.Me].url | 0 B | ||
| [DesireCourse.Net].url | 0 B | ||
| [FreeCourseWorld.Com].url | 102 B | ||
| ▲ 199 total files | |||
Artificial Intelligence: Reinforcement Learning in Python
Complete guide to artificial intelligence and machine learning, prep for deep reinforcement learning
For More Courses Visit: https://desirecourse.net
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 1.8 GB | freecoursewb | 2 weeks | 13 | 11 | |
| 2 GB | freecoursewb | 3 weeks | 27 | 34 | |
| 1.9 GB | freecoursewb | 1 month | 5 | 3 | |
| 2 GB | freecoursewb | 2 months | 15 | 8 | |
| 1.5 GB | freecoursewb | 2 months | 2 | 8 |
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