Apress - Artificial Neural Networks With Java (2019 EN)

Discussion in 'Artificial intelligence' started by Kanka, Aug 16, 2019.

  1. Kanka

    Kanka Well-Known Member Loyal User

    Messages:
    10,157
    Likes Received:
    264
    Trophy Points:
    83
    [​IMG]

    Author: Igor Livshin
    Full Title: Artificial Neural Networks With Java: Tools For Building Neural Network Applications
    Publisher: Apress; 1st ed. edition (April 13, 2019)
    Year: 2019
    ISBN-13: 9781484244210 (978-1-4842-4421-0), 9781484244203 (978-1-4842-4420-3)
    ISBN-10: 1484244214, 1484244206
    Pages: 566
    Language: English
    Genre: Educational: Machine learning
    File type: PDF (True)
    Quality: 10/10
    Price: 37.44 €


    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. Artificial Neural Networks with Java also teaches you how to prepare the data to be used in neural network development and suggests various techniques of data preparation for many unconventional tasks.

    The next big topic discussed in the book is using Java for neural network processing. You will use the Encog Java framework and discover how to do rapid development with Encog, allowing you to create large-scale neural network applications.

    The book also discusses the inability of neural networks to approximate complex non-continuous functions, and it introduces the micro-batch method that solves this issue. The step-by-step approach includes plenty of examples, diagrams, and screen shots to help you grasp the concepts quickly and easily.


    Learn:
    ✓ Prepare your data for many different tasks
    ✓ Carry out some unusual neural network tasks
    ✓ Create neural network to process non-continuous functions
    ✓ Select and improve the development model

    Features:
    ✓ Explains neural network development in the Java environment
    ✓ Shows examples of manual network processing
    ✓ Discusses solutions to unconventional neural network processing

    Who This Book Is For:
    Intermediate machine learning and deep learning developers who are interested in switching to Java.

    -------------
     

Share This Page