Udemy - Practical Reinforcement Learning using Python - 8 AI Agents

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Practical Reinforcement Learning using Python - 8 AI Agents [TutsNode.com] - Practical Reinforcement Learning using Python - 8 AI Agents 5. Mario Reinforcement Learning Agent
  • 11. Creating a Better Learning Environment for Agent.mp4 (157.9 MB)
  • 11. Creating a Better Learning Environment for Agent.srt (18.2 KB)
  • 10. Learn Function.srt (14.5 KB)
  • 9. Preprocess State for Neural Network Function.srt (10.5 KB)
  • 13. Visualizing our Agent.srt (7.5 KB)
  • 5. Building Neural Network.srt (7.4 KB)
  • 12. Save & Load Agent.srt (5.3 KB)
  • 8. Train Function.srt (5.2 KB)
  • 4. Building Class for Mario Agent.srt (5.1 KB)
  • 2. Importing Packages.srt (5.0 KB)
  • 3. Setting up Gym Environment.srt (3.9 KB)
  • 6. Act Function.srt (3.8 KB)
  • 1. Setting up Project & Installing Python Packages.srt (2.9 KB)
  • 7. Update Epsilon Function.srt (2.2 KB)
  • 10. Learn Function.mp4 (89.0 MB)
  • 9. Preprocess State for Neural Network Function.mp4 (75.4 MB)
  • 13. Visualizing our Agent.mp4 (67.2 MB)
  • 12. Save & Load Agent.mp4 (51.8 MB)
  • 5. Building Neural Network.mp4 (39.6 MB)
  • 8. Train Function.mp4 (29.6 MB)
  • 4. Building Class for Mario Agent.mp4 (28.0 MB)
  • 6. Act Function.mp4 (23.8 MB)
  • 3. Setting up Gym Environment.mp4 (18.9 MB)
  • 2. Importing Packages.mp4 (16.9 MB)
  • 7. Update Epsilon Function.mp4 (16.8 MB)
  • 1. Setting up Project & Installing Python Packages.mp4 (16.7 MB)
4. Flappy Bird Reinforcement Learning Agent
  • 8. Learn Function.srt (16.3 KB)
  • 7. Train Function.srt (10.5 KB)
  • 8. Learn Function.mp4 (143.2 MB)
  • 3. Building class for Flappy Bird Agent.srt (9.4 KB)
  • 5. Building Neural Network.srt (9.4 KB)
  • 10. Visualize Trained Agent.srt (7.8 KB)
  • 9. Visualize Function.srt (5.1 KB)
  • 6. Acting Function.srt (4.4 KB)
  • 2. Importing Packages.srt (4.2 KB)
  • 1. Setting up Project & Installing Python Packages.srt (3.6 KB)
  • 4. What is Deep Q Learning .srt (3.4 KB)
  • 7. Train Function.mp4 (78.2 MB)
  • 5. Building Neural Network.mp4 (70.4 MB)
  • 10. Visualize Trained Agent.mp4 (61.3 MB)
  • 3. Building class for Flappy Bird Agent.mp4 (43.8 MB)
  • 9. Visualize Function.mp4 (33.3 MB)
  • 6. Acting Function.mp4 (31.7 MB)
  • 1. Setting up Project & Installing Python Packages.mp4 (24.3 MB)
  • 2. Importing Packages.mp4 (19.4 MB)
  • 4. What is Deep Q Learning .mp4 (9.9 MB)
3. Autonomous Taxi Agent
  • 7. Visualizing our Agent & Testing in other Environments.srt (12.8 KB)
  • 5. Training Q-Learning Agent.srt (11.8 KB)
  • 3. What is Q-Learning.srt (9.3 KB)
  • 1. Setting up Project & Installing Python Packages.srt (2.7 KB)
  • 6. Analyzing our Trained Agent.srt (2.5 KB)
  • 4. Implementing Q-Learning from Scratch.srt (5.2 KB)
  • 2. Importing Packages & Setting up Gym Environment.srt (5.2 KB)
  • 7. Visualizing our Agent & Testing in other Environments.mp4 (98.4 MB)
  • 5. Training Q-Learning Agent.mp4 (68.4 MB)
  • 3. What is Q-Learning.mp4 (49.4 MB)
  • 4. Implementing Q-Learning from Scratch.mp4 (21.6 MB)
  • 2. Importing Packages & Setting up Gym Environment.mp4 (20.5 MB)
  • 6. Analyzing our Trained Agent.mp4 (14.9 MB)
  • 1. Setting up Project & Installing Python Packages.mp4 (9.6 MB)
2. SpaceInvaders Agent
  • 3. Building Neural Network.srt (11.3 KB)
  • 2. Importing Packages & Setting up Gym Environment.srt (9.5 KB)
  • 7. Save & Load Agent.srt (1.7 KB)
  • 4. Building Reinforcement Learning Agent.srt (8.1 KB)
  • 1. Setting up for Course & Installing Python Packages.srt (7.7 KB)
  • 6. Visualizing our Agent.srt (5.4 KB)
  • 5. Training Agent.srt (4.1 KB)
  • 4. Building Reinforcement Learning Agent.mp4 (52.7 MB)
  • 3. Building Neural Network.mp4 (50.7 MB)
  • 1. Setting up for Course & Installing Python Packages.mp4 (50.3 MB)
  • 2. Importing Packages & Setting up Gym Environment.mp4 (44.4 MB)
  • 6. Visualizing our Agent.mp4 (33.6 MB)
  • 5. Training Agent.mp4 (21.4 MB)
  • 7. Save & Load Agent.mp4 (8.8 MB)
7. Car Reinforcement Learning Agents
  • 2. Importing Packages.srt (2.4 KB)
  • 6. Agent 2) Training our Agent.srt (8.1 KB)
  • 4. Agent 1) Training & Visualizing our Agent.srt (6.2 KB)
  • 8. Agent 3) Highway Agent.srt (5.7 KB)
  • 1. Setting up Project & Installing Python Packages.srt (5.5 KB)
  • 3. Agent 1) Setting up Roundabout Gym Environment.srt (3.1 KB)
  • 5. Agent 2) Setting up Parking Gym Environment.srt (1.6 KB)
  • 7. Agent 2) Visualizing our Agent.srt (1.1 KB)
  • 6. Agent 2) Training our Agent.mp4 (81.1 MB)
  • 1. Setting up Project & Installing Python Packages.mp4 (50.3 MB)
  • 8. Agent 3) Highway Agent.mp4 (39.8 MB)
  • 4. Agent 1) Training & Visualizing our Agent.mp4 (37.7 MB)
  • 3. Agent 1) Setting up Roundabout Gym Environment.mp4 (25.7 MB)
  • 5. Agent 2) Setting up Parking Gym Environment.mp4 (12.2 MB)
  • 7. Agent 2) Visualizing our Agent.mp4 (8.3 MB)
  • 2. Importing Packages.mp4 (7.6 MB)
6. Stocks Reinforcement Learning Agents
  • 7. Creating Model & Learning from Environment.srt (9.7 KB)
  • 9. PART 2 Implementing 89 different Technical Indicators in Data.srt (6.9 KB)
  • 5. Creating our Environment.srt (6.6 KB)
  • 10. PART 2 Creating Environment with Technical Indicators.srt (6.4 KB)
  • 1. Setting up Project & Installing Python Packages.srt (6.3 KB)
  • 3. Getting our S&P 500 Data.srt (5.6 KB)
  • 11. PART 2 Visualizing our Agent in TA Environment.srt (4.8 KB)
  • 4. Preprocessing our Data.srt (4.5 KB)
  • 8. Visualizing our Agent.srt (3.7 KB)
  • 6. Taking Random Actions in Environment.srt (2.8 KB)
  • 2. Importing Packages.srt (1.9 KB)
  • 7. Creating Model & Learning from Environment.mp4 (71.0 MB)

Description


Description

Join the most comprehensive Reinforcement Learning course on Udemy and learn how to build Amazing Reinforcement Learning Applications!

Do you want to learn how to build cutting edge trading algorithms that leverage todays technology? Or do you want to learn the tools and skills that are considered the state of the art of Artificial Intelligence? Or do you just want to learn Reinforcement Learning in a Highly practical way?

After completing this course you will be able to:

Build any reinforcement learning algorithm in any environment
Use Reinforcement Learning for your own scientific experiments
Solve problems using Reinforcement Learning
Leverage Cutting Edge Technologies for your own project
Master OpenAI gym’s

Why should you choose this course?

This course guides you through a step-by-step process of building state of the art trading algorithms and ensures that you walk away with the practical skills to build any reinforcement learning algorithm idea you have and implement it efficiently.

Here’s what’s included in the course:

Atari Reinforcement Learning Agent
Build Q-Learning from scratch and implement it in Autonomous Taxi Environment
Build Deep Q-Learning from scratch and implement it in Flappy Bird
Build Deep Q-Learning from scratch and implement it in Mario
Build a Stock Reinforcement Learning Algorithm
Build a intelligent car that can complete various environments
And much more!

This course is for you if …

You’re interested in cutting edge technology and applying it in practical ways
You’re passionate about Deep Learning/AI
Want to learn about cutting-edge technologies!
Want to learn reinforcement learning by doing cool projects!

Course prerequisites:

Python!

Who this course is for:

Python Developers
Coding Enthusiast
People Interested in Cutting-Edge Technology

Requirements

Just Python!!
Knowing Neural Networks, but not necessary

Last Updated 4/2021



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Udemy - Practical Reinforcement Learning using Python - 8 AI Agents

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2.4 GB
seeders:21
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Udemy - Practical Reinforcement Learning using Python - 8 AI Agents

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