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Hands-On Data Science and Python Machine Learning

You're reading from   Hands-On Data Science and Python Machine Learning Perform data mining and machine learning efficiently using Python and Spark

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787280748
Length 420 pages
Edition 1st Edition
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Author (1):
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Frank Kane Frank Kane
Author Profile Icon Frank Kane
Frank Kane
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Table of Contents (11) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Statistics and Probability Refresher, and Python Practice 3. Matplotlib and Advanced Probability Concepts 4. Predictive Models 5. Machine Learning with Python 6. Recommender Systems 7. More Data Mining and Machine Learning Techniques 8. Dealing with Real-World Data 9. Apache Spark - Machine Learning on Big Data 10. Testing and Experimental Design

Spark introduction

Let's get started with a high-level overview of Apache Spark and see what it's all about, what it's good for, and how it works.

What is Spark? Well, if you go to the Spark website, they give you a very high-level, hand-wavy answer, "A fast and general engine for large-scale data processing." It slices, it dices, it does your laundry. Well, not really. But it is a framework for writing jobs or scripts that can process very large amounts of data, and it manages distributing that processing across a cluster of computing for you. Basically, Spark works by letting you load your data into these large objects called Resilient Distributed Data stores, RDDs. It can automatically perform operations that transform and create actions based on those RDDs, which you can think of as large data frames.

The beauty of it is that Spark will automatically...

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