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Practical Machine Learning

You're reading from   Practical Machine Learning Learn how to build Machine Learning applications to solve real-world data analysis challenges with this Machine Learning book – packed with practical tutorials

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Product type Paperback
Published in Jan 2016
Publisher Packt
ISBN-13 9781784399689
Length 468 pages
Edition 1st Edition
Languages
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Author (1):
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Sunila Gollapudi Sunila Gollapudi
Author Profile Icon Sunila Gollapudi
Sunila Gollapudi
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Toc

Table of Contents (16) Chapters Close

Preface 1. Introduction to Machine learning FREE CHAPTER 2. Machine learning and Large-scale datasets 3. An Introduction to Hadoop's Architecture and Ecosystem 4. Machine Learning Tools, Libraries, and Frameworks 5. Decision Tree based learning 6. Instance and Kernel Methods Based Learning 7. Association Rules based learning 8. Clustering based learning 9. Bayesian learning 10. Regression based learning 11. Deep learning 12. Reinforcement learning 13. Ensemble learning 14. New generation data architectures for Machine learning Index

Machine learning solution architecture for big data (employing Hadoop)

In this section, let us look at the essential architecture components for implementing a Machine learning solution considering big data requirements.

The proposed solution architecture should support the consumption of a variety of data sources in an efficient and cost-effective way. The following figure summarizes the core architecture components that should potentially be a part of the Machine learning solution technology stack. The choice of frameworks can either be open source or packaged license options. In the context of this book, we consider the latest version of open source (Apache) distribution of Hadoop and its ecosystem components.

Note

Vendor specific frameworks and extensions are out of scope for this chapter.

Machine learning solution architecture for big data (employing Hadoop)

In the next sections, we'll discuss in detail each of these Reference Architecture layers and the required frameworks in each layer.

The Data Source layer

The Data Source layer forms a critical part...

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