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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

Searching wikipedia with Spark MLlib

We're going to build an actual working search algorithm for a piece of Wikipedia using Apache Spark in MLlib, and we're going to do it all in less than 50 lines of code. This might be the coolest thing we do in this entire book!

Go into your course materials and open up the TF-IDF.py script, and that should open up Canopy with the following code:

Now, step back for a moment and let it sink in that we're actually creating a working search algorithm, along with a few examples of using it in less than 50 lines of code here, and it's scalable. I could run this on a cluster. It's kind of amazing. Let's step through the code.

Import statements

We're going to...

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