Hello fellow Geeks! Today, we have some exciting news for you! Java Code Geeks and Packt have teamed up to offer you weekly discounts on their extensive library of books.
This week, we are offering discounts on three books to help you understand and master Java for Data Science. Check them out!
Java Data Analysis
By John R. Hubbard
Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the aim of discovering useful information. Java is one of the most popular languages to perform your data analysis tasks.
This book will help you learn the tools and techniques in Java to conduct data analysis without any hassle. After getting a quick overview of what data science is and the steps involved in the process, you’ll learn the statistical data analysis techniques and implement them using the popular Java APIs and libraries. Through practical examples, you will also learn the machine learning concepts such as classification and regression.
In the process, you’ll familiarize yourself with tools such as Rapidminer and WEKA and see how these Java-based tools can be used effectively for analysis. You will also learn how to analyze text and other types of multimedia. Learn to work with relational, NoSQL, and time-series data. This book will also show you how you can utilize different Java-based libraries to create insightful and easy to understand plots and graphs.
By the end of this book, you will have a solid understanding of the various data analysis techniques, and how to implement them using Java.
Use the code ORSCH75 at the checkout to save 75% on the RRP of ‘Java Data Analysis ’.
Java for Data Science
By Richard M. Reese and Jennifer L. Reese
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 book, we cover the important data science concepts and how they are supported by Java, as well as the often statistically challenging techniques, to provide you with an understanding of their purpose and application.
The book 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. The next section examines the major categories of data analysis including text, visual, and audio data, followed by a discussion of resources that support parallel implementation.
The final chapter illustrates an in-depth data science problem and provides a comprehensive, Java-based solution. Due to the nature of the topic, simple examples of techniques are presented early followed by a more detailed treatment later in the book. This permits a more natural introduction to the techniques and concepts presented in the book.
Use the code ORSCI75 at the checkout to save 75% on the RRP of ‘Java for Data Science’.
Java Data Science Cookbook
By Rushdi Shams
If you are looking to build data science models that are good for production, Java has come to the rescue. With the aid of strong libraries such as MLlib, Weka, DL4j, and more, you can efficiently perform all the data science tasks you need to.
This unique book provides modern recipes to solve your common and not-so-common data science-related problems. We start with recipes to help you obtain, clean, index, and search data. Then you will learn a variety of techniques to analyze, learn from, and retrieve information from data. You will also understand how to handle big data, learn deeply from data, and visualize data.
Finally, you will work through unique recipes that solve your problems while taking data science to production, writing distributed data science applications, and much more—things that will come in handy at work.
Use the code ORSCJ75 at the checkout to save 75% on the RRP of ‘Java Data Science Cookbook’.