March 2017
Beginner to intermediate
372 pages
6h 42m
English
Overview
Java Data Science Cookbook is a hands-on guide that provides Java developers with practical recipes to carry out essential data science tasks. You will explore MLlib, Weka, and DL4j while tackling topics such as data acquisition, cleaning, analysis, modeling, and visualization. Through step-by-step recipes, you'll gain the skills needed to deploy your data science applications into production securely and efficiently.
What this Book will help me do
- Learn to acquire, clean, and preprocess data to remove noise and outliers, preparing datasets for insightful analysis.
- Master the use of cutting-edge tools like Weka and DL4j for machine learning and deep learning with Java-based environments.
- Develop techniques to index, search, and retrieve data effectively, including handling large-scale data challenges.
- Understand the implementation of big data tools in Java ecosystems like Spark and Hadoop for efficient data computation.
- Advance your data visualization skills to create meaningful insights and communicate results visually in impactful ways.
Author(s)
None Shams is an experienced software engineer and data science practitioner specializing in Java-based technologies. With a career spanning multiple industries, Shams has focused on creating efficient, scalable, and intuitive solutions for complex problems. As an author, Shams is dedicated to delivering actionable, practical knowledge in a clear and approachable style, inspiring developers to advance their skills.
Who is it for?
This book is designed for Java developers looking to expand their abilities into data science. If you already understand the basics of Java programming and want to learn how to leverage the language for data analysis, machine learning, and visualization, this book is for you. It is also appropriate for those who aim to build production-ready solutions that incorporate these data science techniques. Whether you're a professional developer seeking career growth or a student preparing for a role in data science, this book will guide you effectively.
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