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Deep Learning from the Basics

You're reading from   Deep Learning from the Basics Python and Deep Learning: Theory and Implementation

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Product type Paperback
Published in Mar 2021
Publisher Packt
ISBN-13 9781800206137
Length 316 pages
Edition 1st Edition
Languages
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Authors (2):
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Shigeo Yushita Shigeo Yushita
Author Profile Icon Shigeo Yushita
Shigeo Yushita
Koki Saitoh Koki Saitoh
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Koki Saitoh
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Toc

Table of Contents (11) Chapters Close

Preface Introduction 1. Introduction to Python FREE CHAPTER 2. Perceptrons 3. Neural Networks 4. Neural Network Training 5. Backpropagation 6. Training Techniques 7. Convolutional Neural Networks 8. Deep Learning Appendix A

Installing Python

The following section describes some precautions you will need to take when installing Python in your environment (PC).

Python Versions

Python has two major versions: version 2 and version 3. Currently, both are in active use. So, when you install Python, you must carefully choose which version to install. These two versions are not completely compatible (to be accurate, no backward compatibility is available). Some programs written in Python 3 cannot be run in Python 2. This book uses Python 3. If you have only Python 2 installed, installing Python 3 is recommended.

External Libraries That We Use

The goal of this book is to implement Deep Learning from the Basics. So, our policy is that we will use external libraries as little as possible, but we will use the following two libraries by way of exception: NumPy and Matplotlib. We will use these two libraries to implement deep learning efficiently.

NumPy is a library for numerical calculations. It provides many convenient methods for handling advanced mathematical algorithms and arrays (matrices). To implement deep learning in this book, we will use these convenient methods for efficient implementation.

Matplotlib is a library for drawing graphs. You can use Matplotlib to visualize experimental results and visually check the data while executing deep learning. This book uses these libraries to implement deep learning.

This book uses the following programming language and libraries:

  • Python 3
  • NumPy
  • Matplotlib

Now, we will describe how to install Python for those who need to install it. If you have already met these requirements, you can skip this section.

Anaconda Distribution

Although numerous methods are available for installing Python, this book recommends that you use a distribution called Anaconda. Distributions contain the required libraries so that the user can install them collectively. The Anaconda distribution focuses on data analysis. It also contains libraries useful for data analysis, such as NumPy and Matplotlib, as described earlier.

As we mentioned previously, this book uses Python 3. Therefore, you will need to install the Anaconda distribution for Python 3. Use the following link to download the distribution suitable for your OS and install it:

https://docs.anaconda.com/anaconda/install/

You have been reading a chapter from
Deep Learning from the Basics
Published in: Mar 2021
Publisher: Packt
ISBN-13: 9781800206137
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