Regression Analysis with Python
Discover everything you need to know about the art of regression analysis with Python, and change how you view data
Published on 8. July 2025
312 pages
978-1-78398-074-1 (ISBN)
Description
Learn the art of regression analysis with Python
Key Features
[*] Become competent at implementing regression analysis in Python
[*] Solve some of the complex data science problems related to predicting outcomes
[*] Get to grips with various types of regression for effective data analysis
Book DescriptionRegression is the process of learning relationships between inputs and continuous outputs from example data, which enables predictions for novel inputs. There are many kinds of regression algorithms, and the aim of this book is to explain which is the right one to use for each set of problems and how to prepare real-world data for it. With this book you will learn to define a simple regression problem and evaluate its performance. The book will help you understand how to properly parse a dataset, clean it, and create an output matrix optimally built for regression. You will begin with a simple regression algorithm to solve some data science problems and then progress to more complex algorithms. The book will enable you to use regression models to predict outcomes and take critical business decisions. Through the book, you will gain knowledge to use Python for building fast better linear models and to apply the results in Python or in any computer language you prefer.What you will learn
[*] Format a dataset for regression and evaluate its performance
[*] Apply multiple linear regression to real-world problems
[*] Learn to classify training points
[*] Create an observation matrix, using different techniques of data analysis and cleaning
[*] Apply several techniques to decrease (and eventually fix) any overfitting problem
[*] Learn to scale linear models to a big dataset and deal with incremental data
Who this book is forThe book targets Python developers, with a basic understanding of data science, statistics, and math, who want to learn how to do regression analysis on a dataset. It is beneficial if you have some knowledge of statistics and data science.
Key Features
[*] Become competent at implementing regression analysis in Python
[*] Solve some of the complex data science problems related to predicting outcomes
[*] Get to grips with various types of regression for effective data analysis
Book DescriptionRegression is the process of learning relationships between inputs and continuous outputs from example data, which enables predictions for novel inputs. There are many kinds of regression algorithms, and the aim of this book is to explain which is the right one to use for each set of problems and how to prepare real-world data for it. With this book you will learn to define a simple regression problem and evaluate its performance. The book will help you understand how to properly parse a dataset, clean it, and create an output matrix optimally built for regression. You will begin with a simple regression algorithm to solve some data science problems and then progress to more complex algorithms. The book will enable you to use regression models to predict outcomes and take critical business decisions. Through the book, you will gain knowledge to use Python for building fast better linear models and to apply the results in Python or in any computer language you prefer.What you will learn
[*] Format a dataset for regression and evaluate its performance
[*] Apply multiple linear regression to real-world problems
[*] Learn to classify training points
[*] Create an observation matrix, using different techniques of data analysis and cleaning
[*] Apply several techniques to decrease (and eventually fix) any overfitting problem
[*] Learn to scale linear models to a big dataset and deal with incremental data
Who this book is forThe book targets Python developers, with a basic understanding of data science, statistics, and math, who want to learn how to do regression analysis on a dataset. It is beneficial if you have some knowledge of statistics and data science.
All prices
More details
Edition
Digital original
Language
English
Place of publication
Birmingham
United Kingdom
Target group
Professional and scholarly
US School Grade: College Graduate Student
Edition type
Digital original
File size
6,74 MB
ISBN-13
978-1-78398-074-1 (9781783980741)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Luca Massaron | Alberto Boschetti
Regression Analysis with Python
Learn the art of regression analysis with Python
Book
02/2016
Packt Publishing
€56.00
Shipment within 3-4 weeks
Persons
Massaron Luca :
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.Boschetti Alberto :
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.
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.Boschetti Alberto :
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.
Content
Table of Contents
Regression, the workhorse of data science
Approaching Regression: Simple Linear Regression
Multiple Linear Regression
Logistic Regression
Data preparation
Achieving generalization
Online and Batch Learning
Beyond linearity
Real World Applications for Regression Models
Regression, the workhorse of data science
Approaching Regression: Simple Linear Regression
Multiple Linear Regression
Logistic Regression
Data preparation
Achieving generalization
Online and Batch Learning
Beyond linearity
Real World Applications for Regression Models
