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【影视】 Vanessa Vixon in Positive Reinforcement [.wmv]

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【影视】 [DesireCourse.Net] Udemy - Advanced AI Deep Reinforcement Learning in Python

收录时间:2020-01-31 文档个数:149 文档大小:2.5 GB 最近下载:2024-10-04 人气:3173 磁力链接

6. Deep Q-Learning/7. Deep Q-Learning in Tensorflow for Breakout.mp4 246.0 MB
6. Deep Q-Learning/8. Deep Q-Learning in Theano for Breakout.mp4 245.0 MB
9. Appendix FAQ/2. Windows-Focused Environment Setup 2018.mp4 195.2 MB
7. A3C/5. A3C - Code pt 4.mp4 193.3 MB
8. Theano and Tensorflow Basics Review/4. (Review) Tensorflow Neural Network in Code.mp4 102.0 MB
8. Theano and Tensorflow Basics Review/1. (Review) Theano Basics.mp4 97.9 MB
8. Theano and Tensorflow Basics Review/2. (Review) Theano Neural Network in Code.mp4 91.2 MB
7. A3C/4. A3C - Code pt 3.mp4 88.6 MB
8. Theano and Tensorflow Basics Review/3. (Review) Tensorflow Basics.mp4 85.4 MB
9. Appendix FAQ/8. Proof that using Jupyter Notebook is the same as not using it.mp4 82.0 MB
7. A3C/1. A3C - Theory and Outline.mp4 75.2 MB
7. A3C/3. A3C - Code pt 2.mp4 60.4 MB
7. A3C/2. A3C - Code pt 1 (Warmup).mp4 52.5 MB
9. Appendix FAQ/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
9. Appendix FAQ/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.8 MB
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9. Appendix FAQ/12. What order should I take your courses in (part 2).mp4 39.4 MB
9. Appendix FAQ/11. What order should I take your courses in (part 1).mp4 30.7 MB
6. Deep Q-Learning/6. Pseudocode and Replay Memory.mp4 29.2 MB
9. Appendix FAQ/4. How to Code by Yourself (part 1).mp4 25.7 MB

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【影视】 [UdemyCourseDownloader] Advanced AI Deep Reinforcement Learning in Python

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07 Appendix/044 Environment Setup.mp4 46.0 MB
07 Appendix/045 How to Code by Yourself part 1.mp4 25.7 MB
05 Policy Gradients/035 Mountain Car Continuous Tensorflow.mp4 21.1 MB
06 Deep Q-Learning/042 Deep Q-Learning in Theano for Breakout.mp4 21.0 MB
05 Policy Gradients/034 Mountain Car Continuous Theano.mp4 20.0 MB
05 Policy Gradients/030 Policy Gradient in TensorFlow for CartPole.mp4 18.8 MB
05 Policy Gradients/029 Policy Gradient Methods.mp4 18.8 MB
03 OpenAI Gym and Basic Reinforcement Learning Techniques/016 RBF Neural Networks.mp4 17.3 MB
01 Introduction and Logistics/001 Introduction and Outline.mp4 16.6 MB
06 Deep Q-Learning/041 Deep Q-Learning in Tensorflow for Breakout.mp4 16.5 MB
06 Deep Q-Learning/038 Deep Q-Learning in Tensorflow for CartPole.mp4 15.7 MB
07 Appendix/046 How to Code by Yourself part 2.mp4 15.5 MB
03 OpenAI Gym and Basic Reinforcement Learning Techniques/015 CartPole with Bins Code.mp4 15.4 MB
06 Deep Q-Learning/037 Deep Q-Learning Techniques.mp4 15.1 MB
01 Introduction and Logistics/003 How to Succeed in this Course.mp4 15.1 MB
06 Deep Q-Learning/039 Deep Q-Learning in Theano for CartPole.mp4 14.4 MB
03 OpenAI Gym and Basic Reinforcement Learning Techniques/017 RBF Networks with Mountain Car Code.mp4 14.4 MB
05 Policy Gradients/031 Policy Gradient in Theano for CartPole.mp4 14.1 MB
02 Background Review/005 Review of Markov Decision Processes.mp4 12.8 MB
04 TD Lambda/026 TD Lambda.mp4 12.3 MB

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【影视】 [FreeCoursesOnline.Me] Udacity - Deep Reinforcement Learning Nanodegree v1.0.0

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【影视】 Lecture 10 - Reinforcement Learning

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Lecture 10 Segment 4 Model-Free Learning Sample Based - Temporal Difference Learning.mp4 22.8 MB
Lecture 10 Segment 5 Active Reinforcement Learning - Q-Learning.mp4 18.5 MB
Lecture 10 Segment 3 Passive Reinforcement Learning.mp4 17.3 MB
Lecture 10 Segment 1 Reinforcement Learning.mp4 17.3 MB
Lecture 10 Segment 2 Model-Based Learning.mp4 12.7 MB

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【影视】 [FreeCourseSite.com] Udemy - Artificial Intelligence Reinforcement Learning in Python

收录时间:2020-02-08 文档个数:165 文档大小:1.3 GB 最近下载:2024-10-04 人气:3101 磁力链接

9. Appendix/2. Windows-Focused Environment Setup 2018.mp4 195.4 MB
3. Build an Intelligent Tic-Tac-Toe Agent/4. The Value Function and Your First Reinforcement Learning Algorithm.mp4 108.8 MB
4. Markov Decision Proccesses/7. Bellman Examples.mp4 91.3 MB
9. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
2. Return of the Multi-Armed Bandit/7. Bayesian Thompson Sampling.mp4 54.4 MB
9. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
9. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.8 MB
9. Appendix/11. What order should I take your courses in (part 2).mp4 39.4 MB
9. Appendix/10. What order should I take your courses in (part 1).mp4 30.7 MB
9. Appendix/4. How to Code by Yourself (part 1).mp4 25.7 MB
1. Introduction and Outline/2. What is Reinforcement Learning.mp4 23.0 MB
4. Markov Decision Proccesses/5. Value Function Introduction.mp4 20.7 MB
9. Appendix/6. How to Succeed in this Course (Long Version).mp4 19.2 MB
9. Appendix/5. How to Code by Yourself (part 2).mp4 15.5 MB
8. Approximation Methods/9. Course Summary and Next Steps.mp4 13.9 MB
3. Build an Intelligent Tic-Tac-Toe Agent/2. Components of a Reinforcement Learning System.mp4 13.3 MB
5. Dynamic Programming/3. Iterative Policy Evaluation in Code.mp4 12.7 MB
5. Dynamic Programming/2. Gridworld in Code.mp4 12.0 MB
8. Approximation Methods/8. Semi-Gradient SARSA in Code.mp4 11.1 MB
2. Return of the Multi-Armed Bandit/8. Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.mp4 11.1 MB

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【影视】 Packt Hands-on Reinforcement Learning with TensorFlow

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05.Getting Production-Ready with TensorFlow/0502.Structuring the Code Base.mp4 77.8 MB
04.Deep Reinforcement Learning with TensorFlow/0404.DQN in Action.mp4 72.9 MB
05.Getting Production-Ready with TensorFlow/0503.Debugging and Some Nice Practices in TensorFlow.mp4 71.7 MB
05.Getting Production-Ready with TensorFlow/0504.TensorFlow on Multiple Devices.mp4 58.2 MB
04.Deep Reinforcement Learning with TensorFlow/0405.Dueling Double DQN.mp4 55.2 MB
04.Deep Reinforcement Learning with TensorFlow/0403.Implementing DQN.mp4 49.6 MB
03.Balancing a Cartpole Using Q-Networks/0303.TensorFlow Basics.mp4 45.6 MB
02.Training a Smartcab Using Q-Learning/0201.The Taxi-v2 Environment.mp4 43.5 MB
05.Getting Production-Ready with TensorFlow/0501.Logging, Saving, and Visualizing.mp4 41.2 MB
02.Training a Smartcab Using Q-Learning/0205.Q-Learning Agent in Action.mp4 39.6 MB
03.Balancing a Cartpole Using Q-Networks/0304.Implementing Q-Network.mp4 38.4 MB
03.Balancing a Cartpole Using Q-Networks/0301.The Cartpole Environment.mp4 33.5 MB
02.Training a Smartcab Using Q-Learning/0204.Implementing Q-Learning.mp4 31.9 MB
01.Understanding the Reinforcement Learning Framework/0104.Setting Up Environments Using Open AI’s Gym Framework.mp4 29.4 MB
02.Training a Smartcab Using Q-Learning/0202.Operating Taxi-v2 Using a Dumb Agent.mp4 24.3 MB
03.Balancing a Cartpole Using Q-Networks/0305.Q-Network Agent in Action.mp4 18.4 MB
01.Understanding the Reinforcement Learning Framework/0101.The Course Overview.mp4 17.9 MB
03.Balancing a Cartpole Using Q-Networks/0302.Introducing Q-Networks.mp4 16.3 MB
01.Understanding the Reinforcement Learning Framework/0103.Common RL Tasks and the Reinforcement Process.mp4 16.2 MB
05.Getting Production-Ready with TensorFlow/0505.Next Steps.mp4 15.9 MB

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【压缩文件】 [ FreeCourseWeb.com ] Udemy - Deep Reinforcement Learning 2.0- The smartest combination of Deep Q-Learning, Policy Gradient, Actor Critic, and DDPG.zip

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[ FreeCourseWeb.com ] Udemy - Deep Reinforcement Learning 2.0- The smartest combination of Deep Q-Learning, Policy Gradient, Actor Critic, and DDPG.zip 4.9 GB

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【影视】 [FreeCourseLab.com] Udemy - Advanced AI Deep Reinforcement Learning in Python

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9. Appendix/3. Windows-Focused Environment Setup 2018.mp4 195.2 MB
7. A3C/5. A3C - Code pt 4.mp4 193.3 MB
8. Theano and Tensorflow Basics Review/4. (Review) Tensorflow Neural Network in Code.mp4 102.0 MB
8. Theano and Tensorflow Basics Review/1. (Review) Theano Basics.mp4 97.9 MB
8. Theano and Tensorflow Basics Review/2. (Review) Theano Neural Network in Code.mp4 91.2 MB
7. A3C/4. A3C - Code pt 3.mp4 88.6 MB
8. Theano and Tensorflow Basics Review/3. (Review) Tensorflow Basics.mp4 85.4 MB
9. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
7. A3C/1. A3C - Theory and Outline.mp4 75.2 MB
7. A3C/3. A3C - Code pt 2.mp4 60.4 MB
7. A3C/2. A3C - Code pt 1 (Warmup).mp4 52.5 MB
9. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
9. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
9. Appendix/13. What order should I take your courses in (part 2).mp4 39.4 MB
9. Appendix/12. What order should I take your courses in (part 1).mp4 30.8 MB
9. Appendix/5. How to Code by Yourself (part 1).mp4 25.7 MB
5. Policy Gradients/9. Mountain Car Continuous Theano (v2).mp4 23.3 MB
5. Policy Gradients/7. Mountain Car Continuous Tensorflow.mp4 21.1 MB
6. Deep Q-Learning/7. Deep Q-Learning in Theano for Breakout.mp4 21.0 MB
5. Policy Gradients/6. Mountain Car Continuous Theano.mp4 20.0 MB

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【影视】 [FreeCourseLab.com] Udemy - Artificial Intelligence Reinforcement Learning in Python

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10. Appendix/2. Windows-Focused Environment Setup 2018.mp4 195.4 MB
4. Build an Intelligent Tic-Tac-Toe Agent/4. The Value Function and Your First Reinforcement Learning Algorithm.mp4 108.8 MB
5. Markov Decision Proccesses/7. Bellman Examples.mp4 91.3 MB
10. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
2. High Level Overview of Reinforcement Learning and Course Outline/1. What is Reinforcement Learning.mp4 57.3 MB
3. Return of the Multi-Armed Bandit/9. Bayesian Thompson Sampling.mp4 54.4 MB
3. Return of the Multi-Armed Bandit/2. Applications of the Explore-Exploit Dilemma.mp4 53.7 MB
10. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
2. High Level Overview of Reinforcement Learning and Course Outline/1. What is Reinforcement Learning.vtt 45.0 MB
2. High Level Overview of Reinforcement Learning and Course Outline/4. Defining Some Terms.mp4 44.4 MB
10. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
10. Appendix/11. What order should I take your courses in (part 2).mp4 39.4 MB
2. High Level Overview of Reinforcement Learning and Course Outline/2. On Unusual or Unexpected Strategies of RL.mp4 38.9 MB
1. Welcome/1. Introduction.mp4 35.9 MB
2. High Level Overview of Reinforcement Learning and Course Outline/3. Course Outline.mp4 32.5 MB
10. Appendix/10. What order should I take your courses in (part 1).mp4 30.7 MB
10. Appendix/4. How to Code by Yourself (part 1).mp4 25.7 MB
3. Return of the Multi-Armed Bandit/5. Designing Your Bandit Program.mp4 25.7 MB
6. Dynamic Programming/3. Designing Your RL Program.mp4 23.4 MB
4. Build an Intelligent Tic-Tac-Toe Agent/12. Tic Tac Toe Exercise.mp4 20.7 MB

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【影视】 Udacity - Deep Reinforcement Learning Nanodegree nd893 v1.0.0

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【影视】 [CourseClub.NET] Udacity - Deep Reinforcement Learning Nanodegree v1.0.0

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【影视】 Artist Pro Live Sound Reinforcement

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4 - Amplifying the Band.avi 374.8 MB
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3 - Tuning the PA.avi 317.8 MB
5 - The Soundcheck.avi 256.7 MB
1 - Load In.avi 195.3 MB
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6 - Electrical Problems.avi 104.1 MB
7 - Mixing.avi 89.4 MB
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【压缩文件】 Advanced AI Deep Reinforcement Learning in Python

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

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10. Appendix/2. Windows-Focused Environment Setup 2018.mp4 195.4 MB
4. Build an Intelligent Tic-Tac-Toe Agent/4. The Value Function and Your First Reinforcement Learning Algorithm.mp4 108.8 MB
5. Markov Decision Proccesses/7. Bellman Examples.mp4 91.3 MB
10. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
2. High Level Overview of Reinforcement Learning and Course Outline/1. What is Reinforcement Learning.mp4 57.3 MB
3. Return of the Multi-Armed Bandit/9. Bayesian Thompson Sampling.mp4 54.4 MB
3. Return of the Multi-Armed Bandit/2. Applications of the Explore-Exploit Dilemma.mp4 53.7 MB
10. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
2. High Level Overview of Reinforcement Learning and Course Outline/1. What is Reinforcement Learning.vtt 45.0 MB
2. High Level Overview of Reinforcement Learning and Course Outline/4. Defining Some Terms.mp4 44.4 MB
10. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
10. Appendix/11. What order should I take your courses in (part 2).mp4 39.4 MB
2. High Level Overview of Reinforcement Learning and Course Outline/2. On Unusual or Unexpected Strategies of RL.mp4 38.9 MB
1. Welcome/1. Introduction.mp4 35.9 MB
2. High Level Overview of Reinforcement Learning and Course Outline/3. Course Outline.mp4 32.5 MB
10. Appendix/10. What order should I take your courses in (part 1).mp4 30.7 MB
10. Appendix/4. How to Code by Yourself (part 1).mp4 25.7 MB
3. Return of the Multi-Armed Bandit/5. Designing Your Bandit Program.mp4 25.7 MB
6. Dynamic Programming/3. Designing Your RL Program.mp4 23.4 MB
4. Build an Intelligent Tic-Tac-Toe Agent/12. Tic Tac Toe Exercise.mp4 20.7 MB

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【影视】 [FreeCoursesOnline.Me] [Packt] Hands-On Reinforcement Learning with Java [FCO]

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05.Leveraging Monte Carlo Tree Searches and Temporal Difference (TD) in RL/0505.Starting Program and Gathering Results.mp4 47.5 MB
01.Deep Dive into Reinforcement Learning with DL4J RL4J/0101.The Course Overview.mp4 26.6 MB
03.Using Project Malmo Reinforcement Learning Leveraging Dynamic Programming/0304.Configuring RL4J Algorithm for Cliff Walking Problem.mp4 24.6 MB
Exercise Files/exercise_files.zip 22.8 MB
02.Solving Cartpole with Markov Decision Processes (MDPs)/0205.Running Cartpole and Validating Results.mp4 21.1 MB
03.Using Project Malmo Reinforcement Learning Leveraging Dynamic Programming/0305.Starting QLearningDiscreteDense and Saving Results.mp4 20.8 MB
01.Deep Dive into Reinforcement Learning with DL4J RL4J/0102.Main Principles of Reinforcement Learning.mp4 20.4 MB
01.Deep Dive into Reinforcement Learning with DL4J RL4J/0103.Adding DL4J with RL4J to Our Project.mp4 19.1 MB
05.Leveraging Monte Carlo Tree Searches and Temporal Difference (TD) in RL/0503.Configuring Reinforcement Learning Program Using A3C Configuration.mp4 16.1 MB
04.Creating Decision Process for Stock Prediction with Rewards Using Q-Learning/0403.Leveraging QLearningDiscreteDense from RL4J API.mp4 14.7 MB
03.Using Project Malmo Reinforcement Learning Leveraging Dynamic Programming/0303.Loading Cliff Walking Simulation.mp4 14.7 MB
03.Using Project Malmo Reinforcement Learning Leveraging Dynamic Programming/0301.Adding Malmo Library to Our RL4J Project.mp4 14.4 MB
05.Leveraging Monte Carlo Tree Searches and Temporal Difference (TD) in RL/0504.Using A3C Technique with ActorCriticFactorySeparateStdDense.mp4 13.9 MB
02.Solving Cartpole with Markov Decision Processes (MDPs)/0204.Using GymEnv Library from RL4J to Simulate Solution.mp4 13.6 MB
01.Deep Dive into Reinforcement Learning with DL4J RL4J/0105.Configuring Reinforcement Learning Model with QLearning.QLConfiguration.mp4 13.5 MB
04.Creating Decision Process for Stock Prediction with Rewards Using Q-Learning/0404.Performing Stock Prediction Training and Validating Results.mp4 12.6 MB
04.Creating Decision Process for Stock Prediction with Rewards Using Q-Learning/0402.Creating Configuration for Stock Prediction Learning.mp4 10.7 MB
02.Solving Cartpole with Markov Decision Processes (MDPs)/0202.Leveraging Markov Chain in Our Cartpole Solution.mp4 10.5 MB
02.Solving Cartpole with Markov Decision Processes (MDPs)/0203.Using QLConfiguration to Configure Our Model.mp4 9.9 MB
05.Leveraging Monte Carlo Tree Searches and Temporal Difference (TD) in RL/0502.Setting Up A3C Learning Environment.mp4 9.0 MB

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