Book Image

Java for Data Science

By : Richard M. Reese, Jennifer L. Reese
Book Image

Java for Data Science

By: Richard M. Reese, Jennifer L. Reese

Overview of this book

para 1: Get the lowdown on Java and explore big data analytics with Java for Data Science. Packed with examples and data science principles, this book uncovers the techniques & Java tools supporting data science and machine learning. Para 2: The stability and power of Java combines with key data science concepts for effective exploration of data. By working with Java APIs and techniques, this data science book allows you to build applications and use analysis techniques centred on machine learning. Para 3: Java for Data Science gives you the understanding you need to examine the techniques and Java tools supporting big data analytics. These Java-based approaches allow you to tackle data mining and statistical analysis in detail. Deep learning and Java data mining are also featured, so you can explore and analyse data effectively, and build intelligent applications using machine learning. para 4: What?s Inside ? Understand data science principles with Java support ? Discover machine learning and deep learning essentials ? Explore data science problems with Java-based solutions
Table of Contents (19 chapters)
Java for Data Science
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

Chapter 7. Neural Networks

While neural networks have been around for a number of years, they have grown in popularity due to improved algorithms and more powerful machines. Some companies are building hardware systems that explicitly mimic neural networks (https://www.wired.com/2016/05/google-tpu-custom-chips/). The time has come to use this versatile technology to address data science problems.

In this chapter, we will explore the ideas and concepts behind neural networks and then demonstrate their use. Specifically, we will:

  • Define and illustrate neural networks

  • Describe how they are trained

  • Examine various neural network architectures

  • Discuss and demonstrate several different neural networks, including:

    • A simple Java example

    • A Multi Layer Perceptron (MLP) network

    • The k-Nearest Neighbor (k-NN) algorithm and others

The idea for an Artificial Neural Network (ANN), which we will call a neural network, originates from the neuron found in the brain. A neuron is a cell that has dendrites connecting...