[FreeAllCourse.Com] Udemy - Advanced AI Deep Reinforcement Learning in Python

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[FreeAllCourse.Com] Udemy - Advanced AI Deep Reinforcement Learning in Python

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收录时间：2021-04-18
最近下载：2025-02-21

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文件列表

  • 06 Deep Q-Learning/046 Deep Q-Learning in Tensorflow for Breakout.mp4 246.0 MB
  • 06 Deep Q-Learning/047 Deep Q-Learning in Theano for Breakout.mp4 245.0 MB
  • 09 Appendix FAQ/062 Windows-Focused Environment Setup E8.mp4 195.2 MB
  • 07 A3C/054 A3C - Code pt 4.mp4 193.3 MB
  • 08 Theano and Tensorflow Basics Review/060 (Review) Tensorflow Neural Network in Code.mp4 102.0 MB
  • 08 Theano and Tensorflow Basics Review/057 (Review) Theano Basics.mp4 97.9 MB
  • 08 Theano and Tensorflow Basics Review/058 (Review) Theano Neural Network in Code.mp4 91.2 MB
  • 07 A3C/053 A3C - Code pt 3.mp4 88.6 MB
  • 08 Theano and Tensorflow Basics Review/059 (Review) Tensorflow Basics.mp4 85.4 MB
  • 09 Appendix FAQ/068 Proof that using Jupyter Notebook is the same as not using it.mp4 82.0 MB
  • 07 A3C/050 A3C - Theory and Outline.mp4 75.2 MB
  • 07 A3C/052 A3C - Code pt 2.mp4 60.4 MB
  • 07 A3C/051 A3C - Code pt 1 (Warmup).mp4 52.5 MB
  • 09 Appendix FAQ/063 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4 46.0 MB
  • 09 Appendix FAQ/067 Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.8 MB
  • 09 Appendix FAQ/073 BONUS Where to get Udemy coupons and FREE deep learning material.mp4 39.7 MB
  • 09 Appendix FAQ/072 What order should I take your courses in (part 2).mp4 39.4 MB
  • 09 Appendix FAQ/071 What order should I take your courses in (part 1).mp4 30.7 MB
  • 06 Deep Q-Learning/045 Pseudocode and Replay Memory.mp4 29.2 MB
  • 09 Appendix FAQ/064 How to Code by Yourself (part 1).mp4 25.7 MB
  • 05 Policy Gradients/038 Mountain Car Continuous Theano (v2).mp4 23.3 MB
  • 05 Policy Gradients/036 Mountain Car Continuous Tensorflow.mp4 21.1 MB
  • 05 Policy Gradients/035 Mountain Car Continuous Theano.mp4 20.0 MB
  • 01 Introduction and Logistics/004 Tensorflow or Theano - Your Choice.mp4 19.8 MB
  • 05 Policy Gradients/037 Mountain Car Continuous Tensorflow (v2).mp4 19.7 MB
  • 02 Background Review/009 Review of Temporal Difference Learning.mp4 19.4 MB
  • 09 Appendix FAQ/066 How to Succeed in this Course (Long Version).mp4 19.2 MB
  • 05 Policy Gradients/031 Policy Gradient in TensorFlow for CartPole.mp4 18.8 MB
  • 05 Policy Gradients/030 Policy Gradient Methods.mp4 18.8 MB
  • 09 Appendix FAQ/070 Is Theano Dead.mp4 18.7 MB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/017 RBF Neural Networks.mp4 17.3 MB
  • 01 Introduction and Logistics/001 Introduction and Outline.mp4 16.6 MB
  • 06 Deep Q-Learning/042 Deep Q-Learning in Tensorflow for CartPole.mp4 15.7 MB
  • 09 Appendix FAQ/065 How to Code by Yourself (part 2).mp4 15.5 MB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/016 CartPole with Bins (Code).mp4 15.4 MB
  • 06 Deep Q-Learning/041 Deep Q-Learning Techniques.mp4 15.1 MB
  • 06 Deep Q-Learning/043 Deep Q-Learning in Theano for CartPole.mp4 14.4 MB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/018 RBF Networks with Mountain Car (Code).mp4 14.4 MB
  • 05 Policy Gradients/032 Policy Gradient in Theano for CartPole.mp4 14.1 MB
  • 02 Background Review/006 Review of Markov Decision Processes.mp4 12.9 MB
  • 04 TD Lambda/027 TD Lambda.mp4 12.3 MB
  • 02 Background Review/011 Review of Deep Learning.mp4 11.6 MB
  • 06 Deep Q-Learning/049 Deep Q-Learning Section Summary.mp4 10.9 MB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/013 Random Search.mp4 10.8 MB
  • 04 TD Lambda/026 N-Step in Code.mp4 9.9 MB
  • 07 A3C/056 Course Summary.mp4 9.9 MB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/020 RBF Networks with CartPole (Code).mp4 9.3 MB
  • 07 A3C/055 A3C - Section Summary.mp4 9.3 MB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/012 OpenAI Gym Tutorial.mp4 9.1 MB
  • 06 Deep Q-Learning/044 Additional Implementation Details for Atari.mp4 8.9 MB
  • 09 Appendix FAQ/069 Python 2 vs Python 3.mp4 8.2 MB
  • 04 TD Lambda/028 TD Lambda in Code.mp4 8.0 MB
  • 06 Deep Q-Learning/048 Partially Observable MDPs.mp4 8.0 MB
  • 05 Policy Gradients/033 Continuous Action Spaces.mp4 6.9 MB
  • 02 Background Review/007 Review of Dynamic Programming.mp4 6.8 MB
  • 05 Policy Gradients/034 Mountain Car Continuous Specifics.mp4 6.8 MB
  • 02 Background Review/008 Review of Monte Carlo Methods.mp4 6.5 MB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/015 CartPole with Bins (Theory).mp4 6.3 MB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/023 Plugging in a Neural Network.mp4 6.2 MB
  • 06 Deep Q-Learning/040 Deep Q-Learning Intro.mp4 6.2 MB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/021 Theano Warmup.mp4 6.1 MB
  • 09 Appendix FAQ/061 What is the Appendix.mp4 5.7 MB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/024 OpenAI Gym Section Summary.mp4 5.6 MB
  • 01 Introduction and Logistics/002 Where to get the Code.mp4 5.4 MB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/022 Tensorflow Warmup.mp4 5.3 MB
  • 04 TD Lambda/025 N-Step Methods.mp4 5.3 MB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/014 Saving a Video.mp4 4.8 MB
  • 02 Background Review/005 Review Intro.mp4 4.4 MB
  • 02 Background Review/010 Review of Approximation Methods for Reinforcement Learning.mp4 3.8 MB
  • 04 TD Lambda/029 TD Lambda Summary.mp4 3.8 MB
  • 05 Policy Gradients/039 Policy Gradient Section Summary.mp4 3.5 MB
  • 01 Introduction and Logistics/003 How to Succeed in this Course.mp4 3.5 MB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/019 RBF Networks with CartPole (Theory).mp4 3.2 MB
  • 09 Appendix FAQ/067 Is this for Beginners or Experts Academic or Practical Fast or slow-paced.ro.srt 35.8 kB
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  • 06 Deep Q-Learning/046 Deep Q-Learning in Tensorflow for Breakout.ro.srt 32.3 kB
  • 06 Deep Q-Learning/047 Deep Q-Learning in Theano for Breakout.ro.srt 32.1 kB
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  • 06 Deep Q-Learning/047 Deep Q-Learning in Theano for Breakout.it.srt 31.7 kB
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  • 06 Deep Q-Learning/046 Deep Q-Learning in Tensorflow for Breakout.pt.srt 31.0 kB
  • 06 Deep Q-Learning/047 Deep Q-Learning in Theano for Breakout.pt.srt 31.0 kB
  • 06 Deep Q-Learning/046 Deep Q-Learning in Tensorflow for Breakout.pl.srt 30.7 kB
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  • 06 Deep Q-Learning/046 Deep Q-Learning in Tensorflow for Breakout.en.srt 28.8 kB
  • 06 Deep Q-Learning/047 Deep Q-Learning in Theano for Breakout.en.srt 28.8 kB
  • 09 Appendix FAQ/072 What order should I take your courses in (part 2).ro.srt 26.5 kB
  • 09 Appendix FAQ/072 What order should I take your courses in (part 2).es.srt 25.8 kB
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  • 09 Appendix FAQ/064 How to Code by Yourself (part 1).ro.srt 25.4 kB
  • 09 Appendix FAQ/072 What order should I take your courses in (part 2).pl.srt 25.1 kB
  • 09 Appendix FAQ/064 How to Code by Yourself (part 1).pt.srt 24.9 kB
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  • 07 A3C/054 A3C - Code pt 4.ro.srt 23.7 kB
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  • 07 A3C/054 A3C - Code pt 4.es.srt 23.6 kB
  • 07 A3C/054 A3C - Code pt 4.it.srt 23.3 kB
  • 09 Appendix FAQ/064 How to Code by Yourself (part 1).en.srt 23.3 kB
  • 07 A3C/054 A3C - Code pt 4.id.srt 23.1 kB
  • 09 Appendix FAQ/062 Windows-Focused Environment Setup E8.ro.srt 23.0 kB
  • 07 A3C/054 A3C - Code pt 4.pt.srt 22.9 kB
  • 07 A3C/050 A3C - Theory and Outline.ro.srt 22.8 kB
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  • 09 Appendix FAQ/062 Windows-Focused Environment Setup E8.id.srt 22.2 kB
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  • 07 A3C/050 A3C - Theory and Outline.id.srt 22.1 kB
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  • 07 A3C/050 A3C - Theory and Outline.pl.srt 21.9 kB
  • 09 Appendix FAQ/062 Windows-Focused Environment Setup E8.it.srt 21.9 kB
  • 09 Appendix FAQ/062 Windows-Focused Environment Setup E8.pt.srt 21.9 kB
  • 07 A3C/050 A3C - Theory and Outline.it.srt 21.9 kB
  • 07 A3C/054 A3C - Code pt 4.en.srt 21.7 kB
  • 07 A3C/050 A3C - Theory and Outline.en.srt 20.7 kB
  • 09 Appendix FAQ/062 Windows-Focused Environment Setup E8.en.srt 20.6 kB
  • 09 Appendix FAQ/071 What order should I take your courses in (part 1).ro.srt 18.1 kB
  • 09 Appendix FAQ/071 What order should I take your courses in (part 1).es.srt 17.6 kB
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  • 09 Appendix FAQ/071 What order should I take your courses in (part 1).it.srt 17.4 kB
  • 09 Appendix FAQ/071 What order should I take your courses in (part 1).pl.srt 17.4 kB
  • 05 Policy Gradients/030 Policy Gradient Methods.ro.srt 16.8 kB
  • 01 Introduction and Logistics/001 Introduction and Outline.ro.srt 16.5 kB
  • 09 Appendix FAQ/066 How to Succeed in this Course (Long Version).ro.srt 16.5 kB
  • 05 Policy Gradients/030 Policy Gradient Methods.it.srt 16.4 kB
  • 05 Policy Gradients/030 Policy Gradient Methods.es.srt 16.4 kB
  • 09 Appendix FAQ/071 What order should I take your courses in (part 1).en.srt 16.4 kB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/017 RBF Neural Networks.ro.srt 16.2 kB
  • 05 Policy Gradients/030 Policy Gradient Methods.id.srt 16.2 kB
  • 09 Appendix FAQ/063 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.ro.srt 16.2 kB
  • 01 Introduction and Logistics/001 Introduction and Outline.es.srt 16.1 kB
  • 01 Introduction and Logistics/001 Introduction and Outline.it.srt 16.1 kB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/017 RBF Neural Networks.es.srt 16.1 kB
  • 05 Policy Gradients/030 Policy Gradient Methods.pl.srt 16.1 kB
  • 01 Introduction and Logistics/001 Introduction and Outline.id.srt 16.1 kB
  • 05 Policy Gradients/030 Policy Gradient Methods.pt.srt 16.0 kB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/017 RBF Neural Networks.pt.srt 16.0 kB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/017 RBF Neural Networks.it.srt 16.0 kB
  • 01 Introduction and Logistics/001 Introduction and Outline.pl.srt 16.0 kB
  • 09 Appendix FAQ/063 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.es.srt 15.9 kB
  • 09 Appendix FAQ/066 How to Succeed in this Course (Long Version).id.srt 15.9 kB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/017 RBF Neural Networks.pl.srt 15.9 kB
  • 09 Appendix FAQ/063 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.pt.srt 15.8 kB
  • 09 Appendix FAQ/066 How to Succeed in this Course (Long Version).pt.srt 15.8 kB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/017 RBF Neural Networks.id.srt 15.8 kB
  • 09 Appendix FAQ/063 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.pl.srt 15.8 kB
  • 01 Introduction and Logistics/001 Introduction and Outline.pt.srt 15.8 kB
  • 09 Appendix FAQ/063 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.id.srt 15.7 kB
  • 09 Appendix FAQ/063 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.it.srt 15.7 kB
  • 09 Appendix FAQ/066 How to Succeed in this Course (Long Version).es.srt 15.6 kB
  • 09 Appendix FAQ/068 Proof that using Jupyter Notebook is the same as not using it.ro.srt 15.5 kB
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  • 05 Policy Gradients/030 Policy Gradient Methods.en.srt 15.2 kB
  • 03 OpenAI Gym and Basic Reinforcement Learning Techniques/017 RBF Neural Networks.en.srt 15.0 kB
  • 09 Appendix FAQ/066 How to Succeed in this Course (Long Version).en.srt 14.9 kB
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  • 09 Appendix FAQ/063 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.en.srt 14.8 kB
  • 09 Appendix FAQ/065 How to Code by Yourself (part 2).ro.srt 14.7 kB
  • 09 Appendix FAQ/068 Proof that using Jupyter Notebook is the same as not using it.pl.srt 14.7 kB
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  • 09 Appendix FAQ/065 How to Code by Yourself (part 2).pt.srt 14.4 kB
  • 09 Appendix FAQ/070 Is Theano Dead.ro.srt 14.4 kB
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