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.].
Edition: First edition.Description: xii, 376 pages : illustrations ; 24 cm.ISBN: 9781449369415; 1449369413.Other title: Machine learning with Python.Subject(s): Python (Computer program language) | Programming languages (Electronic computers) | Data mining | Data mining | Programming languages (Electronic computers) | Python (Computer program language) | Maschinelles LernenDDC classification: 005.133Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
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E-Book | SKOLKOVO Library Shelves | QA76.73.P98 M85 2016 (Browse shelf) | Available | |||
Book | Skoltech library Shelves | QA76.73.P98 M85 2016 (Browse shelf) | Available | 2000007915 |
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QA76.73 P70 Docker Deep Dive : | QA76.73.P98 G67 2014 High performance Python / | QA76.73.P98 L877 2013 Learning Python / | QA76.73.P98 M85 2016 Introduction to machine learning with Python : | QA76.758 .R467 2012 Research methodologies, innovations, and philosophies in software systems engineering and information systems / | QA76.76.A65 S255 2011 CUDA by example : | QA76.76.C69 H37 2003 Configuration management. Theory, Practice, and Application / |
Includes index.
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.
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. --
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