The Library of Congress > Linked Data Service > BIBFRAME Works

Bibframe Work

Title
Introduction to machine learning with R : rigorous mathematical analysis
Type
Text
Contribution
Burger, Scott V., (Author)
Subject
Machine learning (LCSH)
R (Computer program language) (LCSH)
Statistics--Data processing (LCSH)
Machine learning. (FAST)
R (Computer program language) (FAST)
Statistics--Data processing. (FAST)
Language
English
Illustrative Content
Illustrations
Classification
LCC: Q325.5 .B85 2018
DDC: 006.31 full
Supplementary Content
index
Content
text
Summary
Machine learning can be a difficult subject if you're not familiar with the basics. With this book, you'll get a solid foundation of introductory principles used in machine learning with the statistical programming language R. You'll start with the basics like regression, then move into more advanced topics like neural networks, and finally delve into the frontier of machine learning in the R world with packages like Caret. By developing a familiarity with topics like understanding the difference between regression and classification models, you'll be able to solve an array of machine learning problems. Knowing when to use a specific model or not can mean the difference between a highly accurate model and a completely useless one. This book provides copious examples to build a working knowledge of machine learning. Understand the major parts of machine learning algorithms Recognize how machine learning can be used to solve a problem in a simple manner Figure out when to use certain machine learning algorithms versus others Learn how to operationalize algorithms with cutting edge packages
Table Of Contents
What is a model?
Supervised and unsupervised machine learning
Sampling statistics and model training in R
Regression in a nutshell
Neural networks in a nutshell
Tree-based methods
Other advanced methods
Machine learning with the caret package
Encyclopedia of machine learning models in caret.
Authorized Access Point
Burger, Scott V., Introduction to machine learning with R : rigorous mathematical analysis