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

Data acquisition using Twitter


The Twitter API is used in conjunction with HBC's HTTP client to acquire tweets, as previously illustrated in the Handling Twitter section of Chapter 2, Data Acquisition. This process involves using the public stream API at the default access level to pull a sample of public tweets currently streaming on Twitter. We will refine the data based on user-selected keywords.

To begin, we declare the TwitterStream class. It consists of two instance variables, (numberOfTweets and topic), two constructors, and a stream method. The numberOfTweets variable contains the number of tweets to select and process, and topic allows the user to search for tweets related to a specific topic. We have set our default constructor to pull 100 tweets related to Star Wars:

public class TwitterStream { 
    private int numberOfTweets; 
    private String topic; 

    public TwitterStream() { 
        this(100, "Stars Wars"); 
    } 

    public TwitterStream(int numberOfTweets, String...