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Java Data Analysis. Data mining, big data analysis, NoSQL, and data visualization

(ebook) (audiobook) (audiobook) Książka w języku 1
Java Data Analysis. Data mining, big data analysis, NoSQL, and data visualization John R. Hubbard - okladka książki

Java Data Analysis. Data mining, big data analysis, NoSQL, and data visualization John R. Hubbard - okladka książki

Java Data Analysis. Data mining, big data analysis, NoSQL, and data visualization John R. Hubbard - audiobook MP3

Java Data Analysis. Data mining, big data analysis, NoSQL, and data visualization John R. Hubbard - audiobook CD

Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
412
Dostępne formaty:
     PDF
     ePub
     Mobi
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.

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O autorze książki

John R. Hubbard has been doing computer-based data analysis for over 40 years at colleges and universities in Pennsylvania and Virginia. He holds an MSc in computer science from Penn State University and a PhD in mathematics from the University of Michigan. He is currently a professor of mathematics and computer science, Emeritus, at the University of Richmond, where he has been teaching data structures, database systems, numerical analysis, and big data. Dr. Hubbard has published many books and research papers, including six other books on computing. Some of these books have been translated into German, French, Chinese, and five other languages. He is also an amateur timpanist.

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