[Tutorialsplanet.NET] Udemy - Artificial Intelligence Reinforcement Learning in Python

Torrent Hash:
08754A2FD2A4E88C8746EA5804E7C4A6F9545715
Number of Files:
177
Content Size:
1.51GB
Convert On:
2023-03-09
Magnet Link:
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File Name
Size
1. Welcome/1. Introduction.mp4
34.25MB
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1. Welcome/1. Introduction.vtt
3.93KB
1. Welcome/2. Where to get the Code.mp4
4.46MB
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1. Welcome/2. Where to get the Code.vtt
4.92KB
1. Welcome/3. Strategy for Passing the Course.mp4
9.47MB
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1. Welcome/3. Strategy for Passing the Course.vtt
10.66KB
10. Appendix/1. What is the Appendix.mp4
5.46MB
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10. Appendix/1. What is the Appendix.vtt
3.38KB
10. Appendix/10. What order should I take your courses in (part 1).mp4
29.32MB
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10. Appendix/10. What order should I take your courses in (part 1).vtt
15.16KB
10. Appendix/11. What order should I take your courses in (part 2).mp4
37.62MB
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10. Appendix/11. What order should I take your courses in (part 2).vtt
22.3KB
10. Appendix/12. Where to get discount coupons and FREE deep learning material.mp4
4.03MB
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10. Appendix/12. Where to get discount coupons and FREE deep learning material.vtt
3.3KB
10. Appendix/2. Windows-Focused Environment Setup 2018.mp4
186.39MB
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10. Appendix/2. Windows-Focused Environment Setup 2018.vtt
18.94KB
10. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
43.92MB
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10. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt
16.58KB
10. Appendix/4. How to Code by Yourself (part 1).mp4
24.53MB
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10. Appendix/4. How to Code by Yourself (part 1).vtt
27.34KB
10. Appendix/5. How to Code by Yourself (part 2).mp4
14.8MB
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10. Appendix/5. How to Code by Yourself (part 2).vtt
16.66KB
10. Appendix/6. How to Succeed in this Course (Long Version).mp4
18.32MB
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10. Appendix/6. How to Succeed in this Course (Long Version).vtt
13.71KB
10. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4
38.96MB
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10. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt
29.9KB
10. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4
78.32MB
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10. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.vtt
13.18KB
10. Appendix/9. Python 2 vs Python 3.mp4
7.84MB
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10. Appendix/9. Python 2 vs Python 3.vtt
5.9KB
2. High Level Overview of Reinforcement Learning and Course Outline/1. What is Reinforcement Learning.mp4
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2. High Level Overview of Reinforcement Learning and Course Outline/1. What is Reinforcement Learning.vtt
42.9MB
2. High Level Overview of Reinforcement Learning and Course Outline/2. On Unusual or Unexpected Strategies of RL.mp4
37.1MB
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2. High Level Overview of Reinforcement Learning and Course Outline/2. On Unusual or Unexpected Strategies of RL.vtt
7.5KB
2. High Level Overview of Reinforcement Learning and Course Outline/3. Course Outline.mp4
30.98MB
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2. High Level Overview of Reinforcement Learning and Course Outline/3. Course Outline.vtt
6.06KB
2. High Level Overview of Reinforcement Learning and Course Outline/4. Defining Some Terms.mp4
42.34MB
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2. High Level Overview of Reinforcement Learning and Course Outline/4. Defining Some Terms.vtt
8.74KB
3. Return of the Multi-Armed Bandit/1. Problem Setup and The Explore-Exploit Dilemma.mp4
6.48MB
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3. Return of the Multi-Armed Bandit/1. Problem Setup and The Explore-Exploit Dilemma.vtt
7.12KB
3. Return of the Multi-Armed Bandit/10. Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.mp4
10.58MB
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3. Return of the Multi-Armed Bandit/10. Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.vtt
5.53KB
3. Return of the Multi-Armed Bandit/11. Nonstationary Bandits.mp4
7.49MB
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3. Return of the Multi-Armed Bandit/11. Nonstationary Bandits.vtt
7.09KB
3. Return of the Multi-Armed Bandit/2. Applications of the Explore-Exploit Dilemma.mp4
51.19MB
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3. Return of the Multi-Armed Bandit/2. Applications of the Explore-Exploit Dilemma.vtt
10.28KB
3. Return of the Multi-Armed Bandit/3. Epsilon-Greedy.mp4
2.79MB
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3. Return of the Multi-Armed Bandit/3. Epsilon-Greedy.vtt
2.94KB
3. Return of the Multi-Armed Bandit/4. Updating a Sample Mean.mp4
2.18MB
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3. Return of the Multi-Armed Bandit/4. Updating a Sample Mean.vtt
2KB
3. Return of the Multi-Armed Bandit/5. Designing Your Bandit Program.mp4
24.52MB
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3. Return of the Multi-Armed Bandit/5. Designing Your Bandit Program.vtt
5.38KB
3. Return of the Multi-Armed Bandit/6. Comparing Different Epsilons.mp4
8.02MB
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3. Return of the Multi-Armed Bandit/6. Comparing Different Epsilons.vtt
4.86KB
3. Return of the Multi-Armed Bandit/7. Optimistic Initial Values.mp4
5.13MB
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3. Return of the Multi-Armed Bandit/7. Optimistic Initial Values.vtt
3.04KB
3. Return of the Multi-Armed Bandit/8. UCB1.mp4
8.23MB
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3. Return of the Multi-Armed Bandit/8. UCB1.vtt
7.37KB
3. Return of the Multi-Armed Bandit/9. Bayesian Thompson Sampling.mp4
51.85MB
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3. Return of the Multi-Armed Bandit/9. Bayesian Thompson Sampling.vtt
11.04KB
4. Build an Intelligent Tic-Tac-Toe Agent/1. Naive Solution to Tic-Tac-Toe.mp4
6.12MB
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4. Build an Intelligent Tic-Tac-Toe Agent/1. Naive Solution to Tic-Tac-Toe.vtt
6.58KB
4. Build an Intelligent Tic-Tac-Toe Agent/10. Tic Tac Toe Code Main Loop and Demo.mp4
9.44MB
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4. Build an Intelligent Tic-Tac-Toe Agent/10. Tic Tac Toe Code Main Loop and Demo.vtt
8.39KB
4. Build an Intelligent Tic-Tac-Toe Agent/11. Tic Tac Toe Summary.mp4
8.31MB
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4. Build an Intelligent Tic-Tac-Toe Agent/11. Tic Tac Toe Summary.vtt
9.33KB
4. Build an Intelligent Tic-Tac-Toe Agent/12. Tic Tac Toe Exercise.mp4
19.78MB
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4. Build an Intelligent Tic-Tac-Toe Agent/12. Tic Tac Toe Exercise.vtt
4.01KB
4. Build an Intelligent Tic-Tac-Toe Agent/2. Components of a Reinforcement Learning System.mp4
12.72MB
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13.4KB
4. Build an Intelligent Tic-Tac-Toe Agent/3. Notes on Assigning Rewards.mp4
4.23MB
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4. Build an Intelligent Tic-Tac-Toe Agent/3. Notes on Assigning Rewards.vtt
4.51KB
4. Build an Intelligent Tic-Tac-Toe Agent/4. The Value Function and Your First Reinforcement Learning Algorithm.mp4
103.72MB
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4. Build an Intelligent Tic-Tac-Toe Agent/4. The Value Function and Your First Reinforcement Learning Algorithm.vtt
21.69KB
4. Build an Intelligent Tic-Tac-Toe Agent/5. Tic Tac Toe Code Outline.mp4
5.04MB
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5.87KB
4. Build an Intelligent Tic-Tac-Toe Agent/6. Tic Tac Toe Code Representing States.mp4
4.43MB
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4. Build an Intelligent Tic-Tac-Toe Agent/6. Tic Tac Toe Code Representing States.vtt
4.5KB
4. Build an Intelligent Tic-Tac-Toe Agent/7. Tic Tac Toe Code Enumerating States Recursively.mp4
9.79MB
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10.3KB
4. Build an Intelligent Tic-Tac-Toe Agent/8. Tic Tac Toe Code The Environment.mp4
10.05MB
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10.88KB
4. Build an Intelligent Tic-Tac-Toe Agent/9. Tic Tac Toe Code The Agent.mp4
9.01MB
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4. Build an Intelligent Tic-Tac-Toe Agent/9. Tic Tac Toe Code The Agent.vtt
9.96KB
5. Markov Decision Proccesses/1. Gridworld.mp4
3.36MB
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3.69KB
5. Markov Decision Proccesses/2. The Markov Property.mp4
7.19MB
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7.66KB
5. Markov Decision Proccesses/3. Defining and Formalizing the MDP.mp4
6.64MB
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5. Markov Decision Proccesses/4. Future Rewards.mp4
5.18MB
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5.47KB
5. Markov Decision Proccesses/5. Value Function Introduction.mp4
19.73MB
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14.5KB
5. Markov Decision Proccesses/6. Value Functions.mp4
8.28MB
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11.03KB
5. Markov Decision Proccesses/7. Bellman Examples.mp4
87.12MB
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25.79KB
5. Markov Decision Proccesses/8. Optimal Policy and Optimal Value Function.mp4
3.24MB
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5. Markov Decision Proccesses/8. Optimal Policy and Optimal Value Function.vtt
4.69KB
5. Markov Decision Proccesses/9. MDP Summary.mp4
2.42MB
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6. Dynamic Programming/1. Intro to Dynamic Programming and Iterative Policy Evaluation.mp4
4.84MB
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4.91KB
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8.32MB
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11.47MB
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9.96KB
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12.07MB
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9.32KB
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4.53MB
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4.7KB
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3.17KB
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7.62MB
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5.56KB
6. Dynamic Programming/8. Policy Iteration in Windy Gridworld.mp4
9.11MB
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7.49KB
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6.19MB
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6. Dynamic Programming/9. Value Iteration.vtt
6.36KB
7. Monte Carlo/1. Monte Carlo Intro.mp4
4.97MB
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5.44KB
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8.75MB
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9.83KB
7. Monte Carlo/3. Monte Carlo Policy Evaluation in Code.mp4
7.92MB
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5.57KB
7. Monte Carlo/4. Policy Evaluation in Windy Gridworld.mp4
7.82MB
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4.85KB
7. Monte Carlo/5. Monte Carlo Control.mp4
9.26MB
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9.34KB
7. Monte Carlo/6. Monte Carlo Control in Code.mp4
10.17MB
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7. Monte Carlo/6. Monte Carlo Control in Code.vtt
5.33KB
7. Monte Carlo/7. Monte Carlo Control without Exploring Starts.mp4
4.63MB
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7. Monte Carlo/7. Monte Carlo Control without Exploring Starts.vtt
5.04KB
7. Monte Carlo/8. Monte Carlo Control without Exploring Starts in Code.mp4
8.06MB
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3.32KB
7. Monte Carlo/9. Monte Carlo Summary.mp4
5.72MB
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6.47KB
8. Temporal Difference Learning/1. Temporal Difference Intro.mp4
2.73MB
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3.05KB
8. Temporal Difference Learning/2. TD(0) Prediction.mp4
5.83MB
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5.84KB
8. Temporal Difference Learning/3. TD(0) Prediction in Code.mp4
5.33MB
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3.62KB
8. Temporal Difference Learning/4. SARSA.mp4
8.21MB
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8.85KB
8. Temporal Difference Learning/5. SARSA in Code.mp4
8.82MB
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8. Temporal Difference Learning/5. SARSA in Code.vtt
5.05KB
8. Temporal Difference Learning/6. Q Learning.mp4
4.85MB
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8. Temporal Difference Learning/6. Q Learning.vtt
5.37KB
8. Temporal Difference Learning/7. Q Learning in Code.mp4
5.43MB
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8. Temporal Difference Learning/7. Q Learning in Code.vtt
3.14KB
8. Temporal Difference Learning/8. TD Summary.mp4
3.95MB
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4.27KB
9. Approximation Methods/1. Approximation Intro.mp4
6.47MB
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9. Approximation Methods/1. Approximation Intro.vtt
7.27KB
9. Approximation Methods/2. Linear Models for Reinforcement Learning.mp4
6.47MB
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6.76KB
9. Approximation Methods/3. Features.mp4
6.24MB
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6.34KB
9. Approximation Methods/4. Monte Carlo Prediction with Approximation.mp4
2.85MB
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2.19KB
9. Approximation Methods/5. Monte Carlo Prediction with Approximation in Code.mp4
6.57MB
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3.67KB
9. Approximation Methods/6. TD(0) Semi-Gradient Prediction.mp4
8.36MB
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5.82KB
9. Approximation Methods/7. Semi-Gradient SARSA.mp4
4.7MB
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9. Approximation Methods/7. Semi-Gradient SARSA.vtt
4.98KB
9. Approximation Methods/8. Semi-Gradient SARSA in Code.mp4
10.61MB
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9. Approximation Methods/8. Semi-Gradient SARSA in Code.vtt
4.93KB
9. Approximation Methods/9. Course Summary and Next Steps.mp4
13.25MB
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9. Approximation Methods/9. Course Summary and Next Steps.vtt
14.48KB
[Tutorialsplanet.NET].url
128B

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