Artificial Intelligence 2.0 - AI, Python, DRL + ChatGPT Prize
- CategoryOther
- TypeTutorials
- LanguageEnglish
- Total size3.9 GB
- Uploaded Byfreecoursewb
- Downloads143
- Last checkedJun. 01st '26
- Date uploadedMay. 31st '26
- Seeders 19
- Leechers11
Artificial Intelligence 2.0: AI, Python, DRL + ChatGPT Prize
https://WebToolTip.com
Last updated 5/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.92 GB | Duration: 9h 41m
Build an AI powerful enough to train an ant / spider and half-humanoid to walk and run across a field with the TD3 model
What you'll learn
Q-Learning
Deep Q-Learning
Policy Gradient
Actor Critic
Deep Deterministic Policy Gradient (DDPG)
Twin-Delayed DDPG (TD3)
The Foundation Techniques of Deep Reinforcement Learning
How to implement a state of the art AI model that is over performing the most challenging virtual applications
Requirements
Some maths basics like knowing what is a differentiation or a gradient
A bit of programming knowledge (classes and objects)
Files:
[ WebToolTip.com ] Artificial Intelligence 2.0 - AI, Python, DRL + ChatGPT Prize- Get Bonus Downloads Here.url (0.2 KB) ~Get Your Files Here ! 1 - Part 1 Fundamentals
- 1 - Welcome.mp4 (190.1 MB)
- 10 - Extra Rl Algorithms Map.html (1.1 KB)
- 11 - Get The Materials.html (0.3 KB)
- 12 - Prizes For Learning.html (0.3 KB)
- 2 - Some Resources Before We Start.html (1.0 KB)
- 3 - Extra Learning Path.html (1.3 KB)
- 4 - Qlearning.mp4 (52.6 MB)
- 5 - Deep Qlearning.mp4 (34.8 MB)
- 6 - Policy Gradient.mp4 (32.2 MB)
- 7 - Actorcritic.mp4 (25.0 MB)
- 8 - Taxonomy Of Ai Models.mp4 (28.9 MB)
- 9 - Extra 5 Advantages Of Drl.html (1.5 KB)
- 13 - Introduction And Initialization.mp4 (82.8 MB)
- 14 - The Qlearning Part.mp4 (136.2 MB)
- 15 - The Policy Learning Part.mp4 (268.8 MB)
- 16 - The Whole Training Process.mp4 (21.6 MB)
- 17 - The Whole Code Folder Of The Course With All The Implementations.html (0.7 KB)
- 17 - The Whole Code Folder.txt (0.0 KB)
- 18 - Beginning.mp4 (20.0 MB)
- 19 - Implementation Step 1.mp4 (76.4 MB)
- 20 - Implementation Step 2.mp4 (202.4 MB)
- 21 - Implementation Step 3.mp4 (136.2 MB)
- 22 - Implementation Step 4.mp4 (195.0 MB)
- 23 - Implementation Step 5.mp4 (55.7 MB)
- 24 - Implementation Step 6.mp4 (106.3 MB)
- 25 - Implementation Step 7.mp4 (28.7 MB)
- 26 - Implementation Step 8.mp4 (84.0 MB)
- 27 - Implementation Step 9.mp4 (32.8 MB)
- 28 - Implementation Step 10.mp4 (28.1 MB)
- 29 - Implementation Step 11.mp4 (63.2 MB)
- 30 - Implementation Step 12.mp4 (33.7 MB)
- 31 - Implementation Step 13.mp4 (47.3 MB)
- 32 - Implementation Step 14.mp4 (51.3 MB)
- 33 - Implementation Step 15.mp4 (179.8 MB)
- 34 - Implementation Step 16.mp4 (78.3 MB)
- 35 - Implementation Step 17.mp4 (79.2 MB)
- 36 - Implementation Step 18.mp4 (156.4 MB)
- 37 - Implementation Step 19.mp4 (98.9 MB)
- 38 - Implementation Step 20.mp4 (66.7 MB)
- 39 - Demo Training.mp4 (187.4 MB)
- 40 - Demo Inference.mp4 (124.5 MB)
- 41 - Plan Of Attack.mp4 (6.9 MB)
- 42 - The Neuron.mp4 (64.0 MB)
- 43 - The Activation Function.mp4 (24.5 MB)
- 44 - How Do Neural Networks Work.mp4 (50.5 MB)
- 45 - How Do Neural Networks Learn.mp4 (67.1 MB)
- 46 - Gradient Descent.mp4 (38.8 MB)
- 47 - Stochastic Gradient Descent.mp4 (35.1 MB)
- 48 - Backpropagation.mp4 (32.8 MB)
- 49 - Plan Of Attack.mp4 (9.7 MB)
- 50 - What Is Reinforcement Learning.mp4 (34.0 MB)
- 51 - The Bellman Equation.mp4 (65.7 MB)
- 52 - The Plan.mp4 (11.6 MB)
- 53 - Markov Decision Process.mp4 (65.4 MB)
- 54 - Policy Vs Plan.mp4 (36.7 MB)
- 55 - Living Penalty.mp4 (62.9 MB)
- 56 - Qlearning Intuition.mp4 (40.3 MB)
- 57 - Temporal Difference.mp4 (49.8 MB)
- 58 - Qlearning Visualization.mp4 (81.1 MB)
- 59 - Plan Of Attack.mp4 (5.0 MB)
- 60 - Deep Qlearning Intuition Step 1.mp4 (53.5 MB)
- 61 - Deep Qlearning Intuition Step 2.mp4 (22.9 MB)
- 62 - Experience Replay.mp4 (59.4 MB)
- 63 - Action Selection Policies.mp4 (91.6 MB)
- 64 - Huge Congrats For Completing The Challenge.html (4.0 KB)
- 65 - Bonus Lecture.html (1.8 KB)
- Bonus Resources.txt (0.1 KB)
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