Mastering Machine Learning with R

Advanced prediction, algorithms, and learning methods with R 3.x

Publisher:Packt Publishing Limited

By: Cory Lesmeister, Doug Ortiz and Vikram Dhillon

Paid access

|Jan 2025

E-Book €34.99Institutions €134.95

Description

Master machine learning techniques with R to deliver insights in complex projects

Key Features

Understand and apply machine learning methods using an extensive set of R packages such as XGBOOST
Understand the benefits and potential pitfalls of using machine learning methods such as Multi-Class Classification and Unsupervised Learning
Implement advanced concepts in machine learning with this example-rich guide

Book Description

This book will teach you advanced techniques in machine learning with the latest code in R 3.3.2. You will delve into statistical learning theory and supervised learning; design efficient algorithms; learn about creating Recommendation Engines; use multi-class classification and deep learning; and more.
You will explore, in depth, topics such as data mining, classification, clustering, regression, predictive modeling, anomaly detection, boosted trees with XGBOOST, and more. More than just knowing the outcome, you’ll understand how these concepts work and what they do.
With a slow learning curve on topics such as neural networks, you will explore deep learning, and more. By the end of this book, you will be able to perform machine learning with R in the cloud using AWS in various scenarios with different datasets.

What you will learn

Gain deep insights into the application of machine learning tools in the industry
Manipulate data in R efficiently to prepare it for analysis
Master the skill of recognizing techniques for effective visualization of data
Understand why and how to create test and training data sets for analysis
Master fundamental learning methods such as linear and logistic regression
Comprehend advanced learning methods such as support vector machines
Learn how to use R in a cloud service such as Amazon

Who this book is for

This book is for data science professionals, data analysts, or anyone with a working knowledge of machine learning, with R who now want to take their skills to the next level and become an expert in the field.

A Process for Success
Linear Regression - the Blocking and Tackling of Machine Learning
Logistic Regression and Discriminant Analysis
Advanced Feature Selection in Linear Models
More Classification Techniques - K-Nearest Neighbors and Support Vector Machines
Classification and Regression Trees
Neural Networks and Deep Learning
Cluster Analysis
Principal Components Analysis
Market Basket Analysis, Recommendation Engines, and Sequential Analysis
Creating Ensembles and Multi-Class Classification
Time Series and Causality
Text Mining
R on the Cloud
Appendix A: R Fundamentals
Appendix B: Sources

https://github.com/packtpublishing/mastering-machine-learning-with-r-second-edition

PDF ISBN: 978-1-78728-448-7

Publisher: Packt Publishing Limited

Publication date: 2025

Language: English

Pages: 420

Related subjects:

Computer sciences,