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Regression Analysis with Python

You're reading from  Regression Analysis with Python

Product type Book
Published in Feb 2016
Publisher
ISBN-13 9781785286315
Pages 312 pages
Edition 1st Edition
Languages
Concepts
Authors (2):
Luca Massaron Luca Massaron
Profile icon Luca Massaron
LinkedIn
Having joined Kaggle over 10 years ago, Luca Massaron is a Kaggle Grandmaster in discussions and a Kaggle Master in competitions and notebooks. In Kaggle competitions he reached no. 7 in the worldwide rankings. On the professional side, Luca is a data scientist with more than a decade of experience in transforming data into smarter artifacts, solving real-world problems, and generating value for businesses and stakeholders. He is a Google Developer Expert(GDE) in machine learning and the author of best-selling books on AI, machine learning, and algorithms.
See other products by Luca Massaron
Alberto Boschetti Alberto Boschetti
Profile icon Alberto Boschetti
LinkedIn
Alberto Boschetti is a data scientist with expertise in signal processing and statistics. He holds a Ph.D. in telecommunication engineering and currently lives and works in London. In his work projects, he faces challenges ranging from natural language processing (NLP) and behavioral analysis to machine learning and distributed processing. He is very passionate about his job and always tries to stay updated about the latest developments in data science technologies, attending meet-ups, conferences, and other events.
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Table of Contents (16) Chapters

Regression Analysis with Python
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Regression – The Workhorse of Data Science 2. Approaching Simple Linear Regression 3. Multiple Regression in Action 4. Logistic Regression 5. Data Preparation 6. Achieving Generalization 7. Online and Batch Learning 8. Advanced Regression Methods 9. Real-world Applications for Regression Models Index

Summary

This chapter concludes the long journey around regression methods we have taken throughout this book. We have seen how to deal with different kinds of regression modeling, how to pre-process data, and how to evaluate the results. In the present chapter, we glanced at some cutting-edge techniques. In the next, and last, chapter of the book, we apply regression in real-world examples and invite you to experiment with some concrete examples.

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Authors (2)

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Profile icon Luca Massaron
LinkedIn
Having joined Kaggle over 10 years ago, Luca Massaron is a Kaggle Grandmaster in discussions and a Kaggle Master in competitions and notebooks. In Kaggle competitions he reached no. 7 in the worldwide rankings. On the professional side, Luca is a data scientist with more than a decade of experience in transforming data into smarter artifacts, solving real-world problems, and generating value for businesses and stakeholders. He is a Google Developer Expert(GDE) in machine learning and the author of best-selling books on AI, machine learning, and algorithms.
Read more
See other products by Luca Massaron
Profile icon Alberto Boschetti
LinkedIn
Alberto Boschetti is a data scientist with expertise in signal processing and statistics. He holds a Ph.D. in telecommunication engineering and currently lives and works in London. In his work projects, he faces challenges ranging from natural language processing (NLP) and behavioral analysis to machine learning and distributed processing. He is very passionate about his job and always tries to stay updated about the latest developments in data science technologies, attending meet-ups, conferences, and other events.
See other products by Alberto Boschetti
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