Neural Network Programming with Python: Create your own neural network!

by Max Sharp

This book is a guide on how to implement a neural network in the Python programming language. It begins by giving you a brief overview of neural networks so as to know what they are, where they are used, and how they are implemented. The next step is an exploration of the backpropagation algorithm. This is the algorithm behind the functionality of neural networks, and it involves a forward and backward pass. Numby is a Python library which can be used for the purpose of implementation of a neural network. This library is discussed in this book, and you are guided on how to use it for that purpose. The functionality of neural networks has to be improved. The various ways to improve how a neural network works is also explored. You are then guided on how to implement neural networks with Neupy, another Python library. The following topics are discussed in this - A Brief Overview of Neural Networks - Backpropagation Algorithm - Neural Networks with Numpy - Improving a Neural Network in Python - Neupy - Models in Neural Networks

57 pages, Kindle Edition

Published October 4, 2016

Reviews

[Osama · Rating 1 out of 5]

A waste of time

It's actually unorganized and unexplained long tutorial for building a neural network. The code format is nasty and used fonts are very big. Considering that python indention is very important, this code formatting can turn it into a nightmare to apply it.
It needs more efforts in formatting and explaining in order to be a readable book.