Public MEGA.nz folder Updated 3 days, 10 hours ago

Udemy - deep reinforcement learning a hands-on tutorial in python

Indexed public MEGA.nz folder with 107 files and 7 folders. Last scan: Jul 04, 2026. Review a sample of the indexed contents before opening the source link.

Tags

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Unlock cost

1 credit

Size

1.5 GB

Files

107

Summary of files indexed in this MEGA.nz folder

49 Videos
2 Documents
4 Archives
52 Others

Sample of files included in this MEGA.nz folder

A curated sample of files and folders indexed from this link — not the full listing. Total counts reflect the complete dataset.

Files 107

  • 6. sarsa.mp4
  • 1. summary.mp4
  • 1.1 data.zip.zip
  • 4. q-learning.mp4
  • 1. introduction.mp4
  • 16. run the app.mp4
  • 3. create files.mp4
  • 2. start project.mp4
  • 1. overall design.mp4
  • 2. create project.mp4
  • 2. optimal policy.mp4
  • 7. deep q-network.mp4
  • 2. rl applications.mp4
  • 3. prepare dataset.mp4
  • 2. course structure.mp4
  • 3. bellman equation.mp4
  • 11. sarsa algorithm.html
  • 3. environment setup.mp4
  • 3.1 requirements.txt.txt
  • 14. test training app.mp4
  • 8. create agent class.mp4
  • 13. create training app.mp4
  • 5. step-by-step example.mp4
  • 15. create evaluation app.mp4
  • 5. implement getting data.mp4
  • 6. test build_maze method.mp4
  • 1. markov decision process.mp4
  • 11. implement buy and sell.mp4
  • 12. implement learn method.mp4
  • 10. implement adding states.mp4
  • 7. render and reset methods.mp4
  • 10. implement getting action.mp4
  • 11. implement choosing action.mp4
  • 15. implement plotting results.mp4
  • 12. implement experience replay.mp4
  • 17. run training and evaluation.mp4
  • 5. implement building maze grid.mp4
  • 6. implement getting all states.mp4
  • 8. exploration vs. exploitation.mp4
  • 9. define rl problem - examples.mp4

Showing a sample of 40 out of 107 total files

MEGA.nz link overview

Created
May 11, 2024
Last scan
Jul 04, 2026

About this MEGA link

This page summarizes an indexed public MEGA.nz folder discovered by Meawfy. It combines file and folder counts, size, tags, scan history, and a sample of the indexed contents so you can evaluate the link before opening the original source.