September 2017
Beginner to intermediate
412 pages
8h 55m
English
Overview
This book, "Java Data Analysis" by John R. Hubbard, is your guide to mastering data analysis using Java. Dive into techniques for analyzing a wide variety of data types, including numerical, text, and multimedia data. By using practical examples and popular tools like RapidMiner and WEKA, this book empowers you to turn complex datasets into actionable insights through the power of Java.
What this Book will help me do
- Master the foundational steps for conducting data analysis and visualization in Java.
- Employ libraries such as RapidMiner and WEKA to carry out statistical methods and machine learning techniques.
- Analyze relational, NoSQL, and time-series databases with confidence using Java.
- Create insightful data visualizations using Java-based libraries and tools.
- Develop machine learning models in Java for tasks such as classification and regression.
Author(s)
John R. Hubbard is an experienced software developer and educator specializing in Java programming and data analytics. With years of practical industry experience and a deep passion for teaching, John crafts technical content that bridges theory and application seamlessly. His books are known for their clarity, relevance, and engaging examples that simplify complex topics.
Who is it for?
This book is perfect for students, Java developers, or budding data scientists looking to gain expertise in data analysis using Java. It's particularly ideal for readers who have a basic understanding of Java and a desire to advance in data-related domains. Basic knowledge of statistics would be beneficial but is not mandatory. If you're seeking to leverage Java for implementing data analysis while learning practical techniques, this book is tailored for you.
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