Book Image

Machine Learning in Java - Second Edition

By : AshishSingh Bhatia, Bostjan Kaluza
Book Image

Machine Learning in Java - Second Edition

By: AshishSingh Bhatia, Bostjan Kaluza

Overview of this book

As the amount of data in the world continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of big data and Data Science. The main challenge is how to transform data into actionable knowledge. Machine Learning in Java will provide you with the techniques and tools you need. You will start by learning how to apply machine learning methods to a variety of common tasks including classification, prediction, forecasting, market basket analysis, and clustering. The code in this book works for JDK 8 and above, the code is tested on JDK 11. Moving on, you will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text analysis. By the end of the book, you will have explored related web resources and technologies that will help you take your learning to the next level. By applying the most effective machine learning methods to real-world problems, you will gain hands-on experience that will transform the way you think about data.
Table of Contents (13 chapters)

Machine learning libraries

There are over 70 Java-based open source machine learning projects listed on the MLOSS.org website, and probably many more unlisted projects live at university servers, GitHub, or Bitbucket. In this section, we will review the major libraries and platforms, the kind of problems they can solve, the algorithms they support, and the kind of data they can work with.

Weka

Waikato Environment for Knowledge Analysis (WEKA) is a machine learning library that was developed at the University of Waikato, New Zealand, and is probably the most well-known Java library. It is a general purpose library that is able to solve a wide variety of machine learning tasks, such as classification, regression, and clustering...