This crash-course is about machine Learning & Artificial Intelligence with Unity3D.

Why using Unity3D for Artificial Intelligence?

Unity3D is the perfect environment in order to train your own AIs. Let’s take the example of a Self-driving Car. What you need is complex environments where there are a lots of realistic physical interactions. You could provide these datas from interactions with the real world, but this is extreme inefficient and time consuming.

Since games become more and more realistic you can provide these informations from virtual environments. And for that Unity is perfectly positioned.

So, no matter if you are a game developer who wants to create AIs for games or if you are a hobby researcher who just want to play with machine Learning … The ML-Agents toolkit is the perfect start in order to create your own AIs.

What do we learn in this crash-course?

This course is structured into 4 major sections:

• Introduction
  This section covers everything in order to get a quick start with the ML-Agents Toolkit. You will learn:

  -Set up of the ML-Agents toolkit with Tensorflow
  -What is a neural-network?
  -The Key Components of the Ml-Agents toolkit

• 3D Roller Ball AI

  This lecture will give you a first impression of the Ml-Agents toolkit in practice. You will learn how to set up the environment and all the necessary components in order to train the AI.

• A.I. learns to play Flappy Bird

  Instead wasting your time with playing this game, we will code our own A.I. that learns to play Flappy Bird by using Reinforcement Learning.

  After training the AI is able to achieve an unlimited score in this game.
  

• Self-driving Car

  The Self-driving Car is the probably the most famous example for Artificial Intelligence, so we will cover this as well. To train the Car we will use a technique called Imitation Learning.

  Imitation Learning is special, because this method uses the inputs from a human Player in order to train the neural network.