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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

Summary

In this chapter, we started our journey with building the most important stepping stone of the book - Installing Enthought Canopy. We then moved to installing other libraries and installing different types of packages. We also grasped some of the basics of Python with the help of various Python code. We covered basic concepts such as modules, lists along with Tuples, and eventually moved on to understanding more of Python basics with a better knowledge of functions and looping in Python. Finally, we started with running some of our simple Python scripts.

In the next chapter, we will move on to understand concepts of statistics and probability.

You have been reading a chapter from
Hands-On Data Science and Python Machine Learning
Published in: Jul 2017
Publisher: Packt
ISBN-13: 9781787280748
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