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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
Alberto Boschetti Alberto Boschetti
Profile icon Alberto Boschetti
View More author details

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

Defining a regression problem


Thanks to machine learning algorithms, deriving knowledge from data is possible. Machine learning has solid roots in years of research: it has really been a long journey since the end of the fifties, when Arthur Samuel clarified machine learning as being a "field of study that gives computers the ability to learn without being explicitly programmed."

The data explosion (the availability of previously unrecorded amounts of data) has enabled the widespread usage of both recent and classic machine learning techniques and made them high-performance techniques. If nowadays you can talk by voice to your mobile phone and expect it to answer properly to you, acting as your secretary (such as Siri or Google Now), it is uniquely because of machine learning. The same holds true for every application based on machine learning such as face recognition, search engines, spam filters, recommender systems for books/music/movies, handwriting recognition, and automatic language...

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