Book Image

Java: Data Science Made Easy

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

Java: Data Science Made Easy

By: Richard M. Reese, Jennifer L. Reese, Alexey Grigorev

Overview of this book

Data science is concerned with extracting knowledge and insights from a wide variety of data sources to analyse patterns or predict future behaviour. It draws from a wide array of disciplines including statistics, computer science, mathematics, machine learning, and data mining. In this course, we cover the basic as well as advanced data science concepts and how they are implemented using the popular Java tools and libraries.The course starts with an introduction of data science, followed by the basic data science tasks of data collection, data cleaning, data analysis, and data visualization. This is followed by a discussion of statistical techniques and more advanced topics including machine learning, neural networks, and deep learning. You will examine the major categories of data analysis including text, visual, and audio data, followed by a discussion of resources that support parallel implementation. Throughout this course, the chapters will illustrate a challenging data science problem, and then go on to present a comprehensive, Java-based solution to tackle that problem. You will cover a wide range of topics – from classification and regression, to dimensionality reduction and clustering, deep learning and working with Big Data. Finally, you will see the different ways to deploy the model and evaluate it in production settings. By the end of this course, you will be up and running with various facets of data science using Java, in no time at all. This course contains premium content from two of our recently published popular titles: - Java for Data Science - Mastering Java for Data Science
Table of Contents (29 chapters)
Title Page
Credits
Preface
Free Chapter
1
Module 1
15
Module 2
26
Bibliography

Case study - page prediction


Now we will continue with our running example, the search engine. What we want to do here is to try to predict whether a URL comes from the first page of the search engine results or not. So, it is time to use the material we have covered so far in this chapter.

In Chapter 2,Data Processing Toolbox, we created the following object to store the information about pages:

public class RankedPage { 
    private String url; 
    private int position; 
    private int page; 
    private int titleLength; 
    private int bodyContentLength; 
    private boolean queryInTitle; 
    private int numberOfHeaders; 
    private int numberOfLinks; 
}

First, we can start by adding a few methods to this object, as follows:

  • isHttps: This should tell us if the URL is HTTPS and can be implemented with url.startsWith("https://")
  • isComDomain: This should tells us if the URL belongs to the COM domain and whether we can implement it with url.contains(".com")
  • isOrgDomain, isNetDomain: This...