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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

Predictive Models

In this chapter, we're going to look at what predictive modeling is and how it uses statistics to predict outcomes from existing data. We'll cover real world examples to understand the concepts better. We'll see what regression analysis means and analyze some of its forms in detail. We'll also look at an example which predicts the price of a car for us.

These are the topics that we'll cover in this chapter:

  • Linear regression and how to implement it in Python
  • Polynomial regression, its application and examples
  • Multivariate regression and how to implement it in Python
  • An example we'll build that predicts the price of a car using Python
  • The concept of multi-level models and some things to know about them
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