Udemy - Practical Multi-Armed Bandit Algorithms in Python

磁力链接/BT种子名称

Udemy - Practical Multi-Armed Bandit Algorithms in Python

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种子哈希：31250faf3b1db419620c2aa5d15c6de934aa3c31
文件大小： 1.31G
已经下载：708次
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收录时间：2025-02-24
最近下载：2025-08-01

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文件列表

  • 1. Course Lectures/7. Building A Baseline Agent That Behaves Randomly.mp4 220.5 MB
  • 1. Course Lectures/13. Exploring Intelligently With Softmax Exploration.mp4 178.0 MB
  • 1. Course Lectures/11. Balancing Exploration & Exploitation With Epsilon Greedy Agents.mp4 144.3 MB
  • 1. Course Lectures/3. Implementing Simulated MAB Environments in Python.mp4 134.0 MB
  • 1. Course Lectures/15. Realistic Optimism Under Uncertainties.mp4 125.7 MB
  • 1. Course Lectures/10. Implementing And Analysing A Greedy Agent.mp4 107.7 MB
  • 1. Course Lectures/14. Being Optimistic Under Uncertainties.mp4 100.3 MB
  • 1. Course Lectures/12. Controlling Exploration With A Decay.mp4 91.7 MB
  • 1. Course Lectures/1. Introduction to Reinforcement Learning & Multi-Armed Bandit Problems.mp4 74.0 MB
  • 1. Course Lectures/5. Implementing Incremental Average In Code.mp4 73.1 MB
  • 1. Course Lectures/6. Implementing Incremental Average For Non-Stationary Bandits.mp4 69.2 MB
  • 1. Course Lectures/4. Estimating Action Values Through Sampling.mp4 58.3 MB
  • 1. Course Lectures/8. Why Are The Results Not Repeatable.mp4 31.6 MB
  • 1. Course Lectures/7. Building A Baseline Agent That Behaves Randomly.srt 48.5 kB
  • 1. Course Lectures/3. Implementing Simulated MAB Environments in Python.srt 34.3 kB
  • 1. Course Lectures/13. Exploring Intelligently With Softmax Exploration.srt 28.6 kB
  • 1. Course Lectures/11. Balancing Exploration & Exploitation With Epsilon Greedy Agents.srt 26.3 kB
  • 1. Course Lectures/1. Introduction to Reinforcement Learning & Multi-Armed Bandit Problems.srt 25.9 kB
  • 1. Course Lectures/15. Realistic Optimism Under Uncertainties.srt 21.5 kB
  • 1. Course Lectures/10. Implementing And Analysing A Greedy Agent.srt 20.0 kB
  • 1. Course Lectures/12. Controlling Exploration With A Decay.srt 17.7 kB
  • 1. Course Lectures/5. Implementing Incremental Average In Code.srt 15.9 kB
  • 1. Course Lectures/14. Being Optimistic Under Uncertainties.srt 15.5 kB
  • 1. Course Lectures/6. Implementing Incremental Average For Non-Stationary Bandits.srt 12.8 kB
  • 1. Course Lectures/4. Estimating Action Values Through Sampling.srt 11.8 kB
  • 1. Course Lectures/8. Why Are The Results Not Repeatable.srt 5.3 kB
  • 1. Course Lectures/5.2 incremental_average.py 245 Bytes
  • 1. Course Lectures/6.1 incremental_average.py 242 Bytes
  • 1. Course Lectures/2. Multi-Armed Bandit Problems.html 160 Bytes
  • 1. Course Lectures/9. Using Incremental Average To Estimate Action Values.html 160 Bytes
  • 1. Course Lectures/16. Strategies For Balancing Exploration & Exploitation.html 160 Bytes
  • 1. Course Lectures/3.1 A Google Colab notebook for every code written in this course..html 146 Bytes
  • 1. Course Lectures/5.1 A Google Colab notebook for every code written in this course..html 146 Bytes
  • 1. Course Lectures/6.2 A Google Colab notebook for every code written in this course..html 146 Bytes
  • 1. Course Lectures/7.1 A Google Colab notebook for every code written in this course..html 146 Bytes
  • 1. Course Lectures/8.1 A Google Colab notebook for every code written in this course..html 146 Bytes
  • 1. Course Lectures/10.1 A Google Colab notebook for every code written in this course..html 146 Bytes
  • 1. Course Lectures/11.1 A Google Colab notebook for every code written in this course..html 146 Bytes
  • 1. Course Lectures/12.1 A Google Colab notebook for every code written in this course..html 146 Bytes
  • 1. Course Lectures/13.1 A Google Colab notebook for every code written in this course..html 146 Bytes
  • 1. Course Lectures/14.1 A Google Colab notebook for every code written in this course..html 146 Bytes
  • 1. Course Lectures/15.1 A Google Colab notebook for every code written in this course..html 146 Bytes

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