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Introduction to Machine Learning with Python : A Guide for Data Scientists by Sarah Guido and Andreas C. Müller (2016, Trade Paperback)
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About this product
Product Identifiers
PublisherO'reilly Media, Incorporated
ISBN-101449369413
ISBN-139781449369415
eBay Product ID (ePID)207764802
Product Key Features
Number of Pages398 Pages
LanguageEnglish
Publication NameIntroduction to Machine Learning with Python : a Guide for Data Scientists
Publication Year2016
SubjectProgramming / Algorithms, Natural Language Processing, Programming Languages / Python
TypeTextbook
Subject AreaComputers
AuthorSarah Guido, Andreas C. Müller
FormatTrade Paperback
Dimensions
Item Height0.8 in
Item Weight25 Oz
Item Length9.2 in
Item Width7 in
Additional Product Features
Intended AudienceScholarly & Professional
LCCN2017-394288
Dewey Edition23
IllustratedYes
Dewey Decimal006.31
SynopsisMachine 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 M ller 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. With this book, you'll learn: Fundamental concepts and applications of machine learning Advantages and shortcomings of widely used machine learning algorithms How to represent data processed by machine learning, including which data aspects to focus on Advanced methods for model evaluation and parameter tuning The concept of pipelines for chaining models and encapsulating your workflow Methods for working with text data, including text-specific processing techniques Suggestions for improving your machine learning and data science skills, 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. With this book, you'??ll learn: Fundamental concepts and applications of machine learning Advantages and shortcomings of widely used machine learning algorithms How to represent data processed by machine learning, including which data aspects to focus on Advanced methods for model evaluation and parameter tuning The concept of pipelines for chaining models and encapsulating your workflow Methods for working with text data, including text-specific processing techniques Suggestions for improving your machine learning and data science skills
LC Classification NumberQ325.5
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Most relevant reviews
- Aug 25, 2020
Beginners Machine Learning book
Best elementary book for Data Science and Machine LearningVerified purchase: YesCondition: Pre-owned
- Apr 24, 2025
Exactly as expected - thanks!
Book was as described - thanks!Verified purchase: YesCondition: New
- Oct 07, 2019
Excelente
Texto claro y del nivel requerido, que cumple con las expectativas esperadas.Verified purchase: YesCondition: New
