Abhishek Nandy

Google’s DeepMind and the Future of Reinforcement Learning

This chapter discusses Google DeepMind and Google AlphaGo and then moves on to the future of Reinforcement Learning and compares what’s happening with man versus machine.

Reinforcement Learning Basics

This chapter is a brief introduction to Reinforcement Learning (RL) and includes some key concepts associated with it.

Reinforcement Learning with Keras, TensorFlow, and ChainerRL

This chapter is a brief introduction to Reinforcement Learning (RL) and includes some key concepts associated with it.

Applying Python to Reinforcement Learning

This chapter explores the world of Reinforcement Learning in terms of Python. First we go through Q learning with Python and then cover a more in-depth analysis of Reinforcement Learning. We start off by going through Q learning in terms of Python. Then we describe Swarm intelligence in Python, with an introduction to what exactly Swarm intelligence is. The chapter also covers the Markov decision process (MDP) toolbox.

RL Theory and Algorithms

This chapter covers how Reinforcement Learning works and explains the concepts behind it, including the different algorithms that form the basis of Reinforcement Learning.

Neural Network Basics

The evolvement of artificial intelligence, machine learning, and deep learning has made so many people start asking questions about what exactly the process of machine learning actually is?

Data Visualization in Unity

In this final chapter, we will touch base on how data visualization is implemented in Unity. We conclude the book by visualizing CSV (comma-separated values) data for a good look and feel.

Unity ML-Agents

In this chapter, we will study how Unity ML-Agents work. First, we will start with a brief description of Unity IDE and then we will look at this feature from Unity. We will check on some demos and then create one simulation of our own. We will see how the agents are trained using Python.

Machine Learning Agents and Neural Network in Unity

In this chapter we will cover the extended Machine Learning Agents v 0.3 in Unity with an example and then move along to creating a neural network in Unity and adding different assets to it.