Regression Analysis with Python - Couverture souple

Alberto Boschetti; Luca Massaron

Couverture souple

ISBN 10 : 1785286315 ISBN 13 : 9781785286315

Editeur : Packt Publishing, 2016

Synopsis

Learn the art of regression analysis with Python

About This Book

• 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

Who This Book Is For

The 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.

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

In Detail

Regression 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.

A propos du livre

À propos des auteurs

Luca Massaron is a Google Developer Expert in machine learning with more than a decade of experience in data science. He is also the author of several best-selling books on AI and a Kaggle master who reached number 7 for his performance in data science competitions.

Alberto Boschetti is a data scientist with expertise in signal processing and statistics. He holds a PhD 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. Connect on LinkedIn at https: //www.linkedin.com/in/alberto-boschetti-a050b55

À propos de la quatrième de couverture

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 Description: Regression 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 for: The 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.

Détails de l'édition

• Éditeur: Packt Publishing
• Date d'édition: 2016
• Langue: anglais
• ISBN 10: 1785286315
• ISBN 13: 9781785286315
• Reliure: Broché
• Nombre de pages: 325
• Coordonnées du fabricant: non disponible
• Personne responsable: gpsr@libri.de; gpsr@libri.de; ; Europaallee 1; Bad Hersfeld; 36244; Allemagne