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Mastering Java Machine Learning

Mastering Java Machine Learning

By : Kamath, Krishna Choppella
3.4 (9)
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Mastering Java Machine Learning

Mastering Java Machine Learning

3.4 (9)
By: Kamath, Krishna Choppella

Overview of this book

Java is one of the main languages used by practicing data scientists; much of the Hadoop ecosystem is Java-based, and it is certainly the language that most production systems in Data Science are written in. If you know Java, Mastering Machine Learning with Java is your next step on the path to becoming an advanced practitioner in Data Science. This book aims to introduce you to an array of advanced techniques in machine learning, including classification, clustering, anomaly detection, stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, deep learning, and big data batch and stream machine learning. Accompanying each chapter are illustrative examples and real-world case studies that show how to apply the newly learned techniques using sound methodologies and the best Java-based tools available today. On completing this book, you will have an understanding of the tools and techniques for building powerful machine learning models to solve data science problems in just about any domain.
Table of Contents (13 chapters)
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10
A. Linear Algebra
12
Index

Batch Big Data Machine Learning


Batch Big Data Machine Learning involves two basic steps, as discussed in Chapter 2, Practical Approach to Real-World Supervised Learning, Chapter 3, Unsupervised Machine Learning Techniques, and Chapter 4, Semi-Supervised and Active Learning: learning or training data from historical datasets and applying the learned models to unseen future data. The following figure demonstrates the two environments along with the component tasks and some technologies/frameworks that accomplish them:

Figure 6: Model time and run time components for Big Data and providers

We will discuss two of the most well-known frameworks for doing Machine Learning in the context of batch data and will use the case study to highlight either the code or tools to perform modeling.

H2O as Big Data Machine Learning platform

H2O (References [13]) is a leading open source platform for Machine Learning at Big Data scale, with a focus on bringing AI to the enterprise. The company was founded in 2011...

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