Introduction to machine learning with Python : a guide for data scientists / Andreas C. Müller and Sarah Guido.

By:

Müller, Andreas C [author.]

Contributor(s):

Guido, Sarah [author.]

Material type: Text

TextPublisher: Sebastopol, CA : Mumbai O'Reilly Media, Inc., SPD 2017Description: xii, 378 pages : illustrations ; 23 cmISBN:

9789352134571

Subject(s):

DDC classification:

005.133 MUL

Contents:

Introduction -- Supervised learning -- Unsupervised learning and preprocessing -- Representing data and engineering features -- Model evaluation and improvement -- Algorithm chains and pipelines -- Working with text data -- Wrapping up.

Summary: Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. -- Provided by publisher.

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Books	H.T. Parekh Library	GSB Collection	005.133 MUL (Browse shelf(Opens below))	Available		B2990

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Previous	005.133 MCK Python for data analysis	005.133 MIT Web scraping with Python :	005.133 MUE Beginning programming with python for dummies	005.133 MUL Introduction to machine learning with Python :	005.133 PAT Hands-on unsupervised learning using Python : how to build applied machine learning solutions from unlabeled data	005.133 PRA Machine Learning Using Python /	005.133 PRA Machine Learning Using Python /	Next

Rs.1200/-
TB2196
Includes index.

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. -- Provided by publisher.

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