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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

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781785880513
Length 556 pages
Edition 1st Edition
Languages
Concepts
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Authors (2):
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Uday Kamath Uday Kamath
Author Profile Icon Uday Kamath
Uday Kamath
Krishna Choppella Krishna Choppella
Author Profile Icon Krishna Choppella
Krishna Choppella
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Table of Contents (13) Chapters Close

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

What are the characteristics of Big Data?


There are many characteristics of Big Data that are different than normal data. Here we highlight them as four Vs that characterize Big Data. Each of these makes it necessary to use specialized tools, frameworks, and algorithms for data acquisition, storage, processing, and analytics:

  • Volume: One of the characteristic of Big Data is the size of the content, structured or unstructured, which doesn't fit the storage capacity or processing power available on a single machine and therefore needs multiple machines.

  • Velocity: Another characteristic of Big Data is the rate at which the content is generated, which contributes to volume but needs to be handled in a time sensitive manner. Social media content and IoT sensor information are the best examples of high velocity Big Data.

  • Variety: This generally refers to multiple formats in which data exists, that is, structured, semi-structured, and unstructured and furthermore, each of them has different forms...

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