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Mastering Java Machine Learning

You're reading from Mastering Java Machine Learning A Java developer's guide to implementing machine learning and big data architectures

Product type Paperback

Published in Jul 2017

Publisher Packt

ISBN-13 9781785880513

Length 556 pages

Edition 1st Edition

Languages

Java

Concepts

Big Data

Authors (2):

Uday Kamath

Krishna Choppella

View More author details

Table of Contents (13) Chapters

Preface

1. Machine Learning Review FREE CHAPTER

2. Practical Approach to Real-World Supervised Learning

3. Unsupervised Machine Learning Techniques

4. Semi-Supervised and Active Learning

5. Real-Time Stream Machine Learning

6. Probabilistic Graph Modeling

7. Deep Learning

8. Text Mining and Natural Language Processing

9. Big Data Machine Learning – The Final Frontier

A. Linear Algebra

B. Probability

Index

Chapter 9. Big Data Machine Learning – The Final Frontier

In recent years, we have seen an exponential growth in data generated by humans and machines. Varied sources, including home sensors, healthcare-related monitoring devices, news feeds, conversations on social media, images, and worldwide commerce transactions—an endless list—contribute to the vast volumes of data generated every day.

Facebook had 1.28 billion daily active users in March 2017 sharing close to four million pieces of unstructured information as text, images, URLs, news, and videos (Source: Facebook). 1.3 billion Twitter users share approximately 500 million tweets a day (Source: Twitter). Internet of Things (IoT) sensors in lights, thermostats, sensor in cars, watches, smart devices, and so on, will grow from 50 billion to 200 billion by 2020 (Source: IDC estimates). YouTube users upload 300 hours of new video content every five minutes. Netflix has 30 million viewers who stream 77,000...

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Authors (2)

Kamath

Kamath

See other products by Kamath

Krishna Choppella

Krishna Choppella

Krishna Choppella builds tools and client solutions in his role as a solutions architect for analytics at BAE Systems Applied Intelligence. He has been programming in Java for 20 years. His interests are data science, functional programming, and distributed computing.

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