Machine learning : a concise introduction / Steven W. Knox.

Format:

Book

Author/Creator:

Knox, Steven W., author.

Series:

Wiley Series in Probability and Statistics

Wiley Series in Probability and Statistics Series

Language:

English

Subjects (All):

Machine learning.

Physical Description:

1 online resource (435 pages)

Edition:

Second edition.

Place of Publication:

Newark : John Wiley & Sons, Incorporated, 2026.

Summary:

New edition of a PROSE award finalist title on core concepts for machine learning, updated with the latest developments in the field, now with Python and R source code side-by-side Machine Learning is a comprehensive text on the core concepts, approaches, and applications of machine learning.

Contents:

Machine learning: a concise introduction

Introduction - examples from real life

The problem of learning

Regression

Classification

Bias-variance trade-off

Combining classifiers

Risk estimation and model selection

Consistency

Clustering

Optimization

High-dimensional data

Communication with clients

Current challenges in machine learning

R and Python source code

List of symbols

The condition number of a matrix with respect to a norm

Converting between normal parameters and level-curve ellipsoids

The geometry of linear functions and linear classifiers

Training data and fitted parameters

Solutions to selected exercises.

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

Description based on publisher supplied metadata and other sources.

ISBN:

1-394-32531-2

1-394-32529-0

9781394325290

OCLC:

1572094430