Neural Networks for Electronics Hobbyists

A Non-Technical Project-Based Introduction



Bookstore > Books > Neural Networks for Electronics Hobbyists

Price$16.29 - $19.99
Rating
AuthorRichard McKeon
PublisherApress
Published2018
Pages139
LanguageEnglish
FormatPaper book / ebook (PDF)
ISBN-101484235061
ISBN-139781484235065
EBook Hardcover Paperback

Learn how to implement and build a neural network with this non-technical, project-based book as your guide. As you work through the chapters, you'll build an electronics project, providing a hands-on experience in training a network.

There are no prerequisites here and you won't see a single line of computer code in this book. Instead, it takes a hardware approach using very simple electronic components. You'll start off with an interesting non-technical introduction to neural networks, and then construct an electronics project. The project isn't complicated, but it illustrates how back propagation can be used to adjust connection strengths or "weights" and train a network.

By the end of this book, you'll be able to take what you've learned and apply it to your own projects. If you like to tinker around with components and build circuits on a breadboard, Neural Networks for Electronics Hobbyists is the book for you.

Gain a practical introduction to neural networks; Review techniques for training networks with electrical hardware and supervised learning; Understand how parallel processing differs from standard sequential programming.





5 5 4

Similar Books


Artificial Neural Networks with Java

Artificial Neural Networks with Java

by Igor Livshin

Use Java to develop neural network applications in this practical book. After learning the rules involved in neural network processing, you will manually process the first neural network example. This covers the internals of front and back propagation, and facilitates the understanding of the main principles of neural network processing. ...

Price:  $23.17  |  Publisher:  Apress  |  Release:  2019

Deep Learning for Natural Language Processing

Deep Learning for Natural Language Processing

by Palash Goyal, Sumit Pandey, Karan Jain

Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models.You'll start by covering the mathematical prerequisites and the fundamentals of deep learning and NLP with...

Price:  $30.01  |  Publisher:  Apress  |  Release:  2018

Learn Keras for Deep Neural Networks

Learn Keras for Deep Neural Networks

by Jojo John Moolayil

Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras.The overall book comprises three ...

Price:  $25.49  |  Publisher:  Apress  |  Release:  2019

Neural Network Programming with Java

Neural Network Programming with Java

by Alan M.F. Souza, Fabio M. Soares

Vast quantities of data are produced every second. In this context, neural networks become a powerful technique to extract useful knowledge from large amounts of raw, seemingly unrelated data. One of the most preferred languages for neural network programming is Java as it is easier to write code using it, and most of the most popular neu...

Price:  $35.99  |  Publisher:  Packt Publishing  |  Release:  2016

Keras Deep Learning Cookbook

Keras Deep Learning Cookbook

by Rajdeep Dua, Manpreet Singh Ghotra

Keras has quickly emerged as a popular deep learning library. Written in Python, it allows you to train convolutional as well as recurrent neural networks with speed and accuracy.The Keras Deep Learning Cookbook shows you how to tackle different problems encountered while training efficient deep learning models, with the help of the popul...

Price:  $34.99  |  Publisher:  Packt Publishing  |  Release:  2018

Applied Deep Learning

Applied Deep Learning

by Umberto Michelucci

Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You'll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid, and Swish), seeing ...

Price:  $22.50  |  Publisher:  Apress  |  Release:  2018

Deep Learning By Example

Deep Learning By Example

by Ahmed Menshawy

Deep learning is a popular subset of machine learning, and it allows you to build complex models that are faster and give more accurate predictions. This book is your companion to take your first steps into the world of deep learning, with hands-on examples to boost your understanding of the topic.This book starts with a quick overview of...

Price:  $31.99  |  Publisher:  Packt Publishing  |  Release:  2018

Deep Learning with TensorFlow, 2nd Edition

Deep Learning with TensorFlow, 2nd Edition

by Giancarlo Zaccone, Md. Rezaul Karim

Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks.This book is conce...

Price:  $31.99  |  Publisher:  Packt Publishing  |  Release:  2018