Book Image

Mastering Java for Data Science

By : Alexey Grigorev
Book Image

Mastering Java for Data Science

By: Alexey Grigorev

Overview of this book

Java is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort. This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrieval and natural language processing, and deep learning and big data. Finally, we finish the book by talking about the ways to deploy the model and evaluate it in production settings.
Table of Contents (17 chapters)
Title Page
About the Author
About the Reviewers
Customer Feedback

Accessing data

By now we already have spent a lot of time describing how to read and write data. But there is much more to that: data often comes in different formats such as CSV, HTML, or JSON or it can be stored in a database. Knowing how to access and process this data is important for Data Science and now we will describe in detail how to do it for the most common data formats and sources.

Text data and CSV

We already have spoken about reading text data in great detail, and it can be done, for example, using the Files helper class from the NIO API or IOUtils from Commons IO.

CSV (Comma Separated Values) is a common way to organize tabular data in plain text files. While it is possible to parse CSV files by hand, there are some corner cases, which make it a bit cumbersome. Luckily, there are nice libraries for that purpose, and one of them is Apache Commons CSV: