Self-driving go-kart with Unity-ML

Description

In this course, you will learn :

• To solve physical problems in simulated environments, configure and use the Unity Machine Learning Agents toolkit.
• About neural networks, supervised and deep reinforcement learning (PPO).
• In Unity, use ML control techniques to teach a go-kart to drive around a track.

Syllabus :

1. Self-driving cars

• Self-driving cars

 

2. Unity Machine Learning Agents

• Self-driving go-kart project in Unity
• Machine Learning Brains
• Control Scripts
• Setup the ML-Agents Toolkit

 

3. Traditional Control

• Traditional Control
• PID Controller
• Tuning
• Heuristic brain in Unity
• Cross-track error
• Testing the PID
• Improvements
• Model-based control
• Onto Machine Learning

 

4. Imitation Learning

• Why Machine Learning
• What kinds of learning
• Neural Networks
• NN Details
• Training a NN
• Optimizer
• Convolutional layers
• Transfer learning
• Imitation learning in Unity
• Training the go-kart via IL
• Testing the drive
• Tips on imitation learning

 

5. Reinforcement Learning

• Reinforcement Learning
• Nomenclature
• Initial state
• Training a policy
• The PPO algorithm
• Evolutional Strategies
• Reward
• Training the go-kart with RL
• Tensorboard analysis
• Testing results

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