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Hands-On Reinforcement Learning with Python

You're reading from Hands-On Reinforcement Learning with Python Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow

Product type Paperback

Published in Jun 2018

Publisher Packt

ISBN-13 9781788836524

Length 318 pages

Edition 1st Edition

Languages

Python

Tools

Deep Reinforcement Learning

Concepts

Deep Reinforcement Learning

Author (1):

Sudharsan Ravichandiran

View More author details

Table of Contents (16) Chapters

Preface

1. Introduction to Reinforcement Learning

2. Getting Started with OpenAI and TensorFlow FREE CHAPTER

3. The Markov Decision Process and Dynamic Programming

4. Gaming with Monte Carlo Methods

5. Temporal Difference Learning

6. Multi-Armed Bandit Problem

7. Deep Learning Fundamentals

8. Atari Games with Deep Q Network

9. Playing Doom with a Deep Recurrent Q Network

10. The Asynchronous Advantage Actor Critic Network

11. Policy Gradients and Optimization

12. Capstone Project – Car Racing Using DQN

13. Recent Advancements and Next Steps

14. Assessments

15. Other Books You May Enjoy

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Artificial neurons

Before understanding ANN, first, let's understand what neurons are and how neurons in our brain actually work. A neuron can be defined as the basic computational unit of the human brain. Our brain contains approximately 100 billion neurons. Each and every neuron is connected through synapses. Neurons receive input from the external environment, sensory organs, or from the other neurons through a branchlike structure called dendrites, as can be seen in the following diagram. These inputs are strengthened or weakened, that is, they are weighted according to their importance and then they are summed together in the soma (cell body). Then, from the cell body, these summed inputs are processed and move through the axons and are sent to the other neurons. The basic single biological neuron is shown in the following diagram:

Now, how do artificial neurons work...

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Authors (1)

Sudharsan Ravichandiran

Sudharsan Ravichandiran

Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.

See other products by Sudharsan Ravichandiran

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