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Regression Analysis Python by Massaron Luca (20 results)
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paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Regression Analysis with Python (Paperback or Softback)
Published by Packt Publishing 2/29/2016, 2016
ISBN 10: 1785286315 ISBN 13: 9781785286315
Language: English
Paperback or Softback. Condition: New. Regression Analysis with Python 1.19. Book.
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Condition: New. pp. 312.
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Regression Analysis with Python: Learn the Art of Regression Analysis With Python
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Regression Analysis with Python
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Regression Analysis with Python: Learn the art of regression analysis with Python
Published by Packt Publishing 2016-02, 2016
ISBN 10: 1785286315 ISBN 13: 9781785286315
Language: English
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Regression Analysis with Python : Learn the Art of Regression Analysis With Python
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Add to basketCondition: New. Über den AutorLuca 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 f.
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Regression Analysis with Python : Learn the Art of Regression Analysis With Python
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Regression Analysis with Python Learn the art of regression analysis with Python
Published by Packt Publishing Limited, 2016
ISBN 10: 1785286315 ISBN 13: 9781785286315
Language: English
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Regression Analysis with Python
Published by Packt Publishing Limited, 2016
ISBN 10: 1785286315 ISBN 13: 9781785286315
Language: English
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Learn the art of regression analysis with PythonKey Features:Become competent at implementing regression analysis in PythonSolve some of the complex data science problems related to predicting outcomesGet to grips with various types of regression for effective data analysisBook 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 performanceApply multiple linear regression to real-world problemsLearn to classify training pointsCreate an observation matrix, using different techniques of data analysis and cleaningApply several techniques to decrease (and eventually fix) any overfitting problemLearn to scale linear models to a big dataset and deal with incremental dataWho 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.
