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Machine learning pocket reference : ...

Harrison, Matt, (1975-)

Machine learning pocket reference : = working with structured data in Python /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Machine learning pocket reference :/ Matt Harrison.
Reminder of title:	working with structured data in Python /
remainder title:	O'Reilly machine learning pocket reference
Author:	Harrison, Matt,
Published:	Beijing ;O'Reilly Media, Inc., : c2019.,
Description:	xiii, 303 p. :ill. ; : 18 cm.;
Notes:	Includes index.
Subject:	Machine learning. -
ISBN:	9781492047544 (pbk.) :

Machine learning pocket reference : = working with structured data in Python /
Harrison, Matt,1975-

Machine learning pocket reference :working with structured data in Python /O'Reilly machine learning pocket referenceMatt Harrison. - 1st ed. - Beijing ;O'Reilly Media, Inc.,c2019. - xiii, 303 p. :ill. ;18 cm.

Includes index.

Introduction -- Overview of the machine learning process -- Classification walkthrough : titanic dataset -- Missing data -- Cleaning data -- Exploring -- Preprocess data -- Feature selection -- Imbalanced classes -- Classification -- Model selection -- Metrics and classification evaluation -- Explaining models -- Regression -- Metrics and regression evaluation -- Explaining regression models -- Dimensionality reduction -- Clustering -- Pipelines.

With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project. Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine learning process and walks you through classification with structured data. You'll also learn methods for clustering, predicting a continuous value (regression), and reducing dimensionality, among other topics. -- Provided by publisher.

ISBN: 9781492047544 (pbk.) :NT740

Nat. Bib. No.: GBB9F1046bnbSubjects--Topical Terms:

561253
Machine learning.

LC Class. No.: Q325.5 / .H37 2019

Dewey Class. No.: 006.3/1

Machine learning pocket reference : = working with structured data in Python /
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260 # $a Beijing ; $a Sebastopol, CA : $b O'Reilly Media, Inc., $c c2019.
300 $a xiii, 303 p. : $b ill. ; $c 18 cm.
500 $a Includes index.
505 0 # $a Introduction -- Overview of the machine learning process -- Classification walkthrough : titanic dataset -- Missing data -- Cleaning data -- Exploring -- Preprocess data -- Feature selection -- Imbalanced classes -- Classification -- Model selection -- Metrics and classification evaluation -- Explaining models -- Regression -- Metrics and regression evaluation -- Explaining regression models -- Dimensionality reduction -- Clustering -- Pipelines.
520 # $a With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project. Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine learning process and walks you through classification with structured data. You'll also learn methods for clustering, predicting a continuous value (regression), and reducing dimensionality, among other topics. -- Provided by publisher.
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650 # 0 $a Python (Computer program language) $3 566246