Mastering Machine Learning with R + code

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Название:Mastering Machine Learning with R

Автор:Cory Lesmeister

Издательство: PASKT

Год: 2015

Страниц: 400

Язык: English

Формат: epub+code

Размер: 7,7 Mb

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

About This Book

Get to grips with the application of Machine Learning methods using an extensive set of R packages

Understand the benefits and potential pitfalls of using machine learning methods

Implement the numerous powerful features offered by R with this comprehensive guide to building an independent R-based ML system

Who This Book Is For

If you want to learn how to use R's machine learning capabilities to solve complex business problems, then this book is for you. Some experience with R and a working knowledge of basic statistical or machine learning will prove helpful.

Table of Contents

1: A Process for Success

2: Linear Regression – The Blocking and Tackling of Machine Learning

3: Logistic Regression and Discriminant Analysis

4: Advanced Feature Selection in Linear Models

5: More Classification Techniques – K-Nearest Neighbors and Support Vector Machines

6: Classification and Regression Trees

7: Neural Networks

8: Cluster Analysis

9: Principal Components Analysis

10: Market Basket Analysis and Recommendation Engines

11: Time Series and Causality

12: Text Mining

What You Will Learn

Gain deep insights to learn the applications of machine learning tools to 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

Familiarize yourself with fundamental learning methods such as linear and logistic regression

Comprehend advanced learning methods such as support vector machines

Realize why and how to apply unsupervised learning methods

In Detail

Machine learning is a field of Artificial Intelligence to build systems that learn from data. Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never been a better time to start applying machine learning to your data.

The book starts with introduction to Cross-Industry Standard Process for Data Mining. It takes you through Multivariate Regression in detail. Moving on, you will also address Classification and Regression trees. You will learn a couple of “Unsupervised techniques.” Finally, the book will walk you through text analysis and time series.

The book will deliver practical and real-world solutions to problems and variety of tasks such as complex recommendation systems.By the end of this book, you will gain expertise in performing R machine learning and will be able to build complex ML projects using R and its packages.

Authors

Cory Lesmeister

Cory Lesmeister currently works as an advanced analytics consultant for Clarity Solution Group, where he applies the methods in this book to solve complex problems and provide actionable insights. Cory spent 16 years at Eli Lilly and Company in sales, market research, Lean Six Sigma, marketing analytics, and new product forecasting. A former U.S. Army Reservist, Cory was in Baghdad, Iraq, in 2009 as a strategic advisor to the 29,000-person Iraqi oil police, where he supplied equipment to help the country secure and protect its oil infrastructure. An aviation aficionado, Cory has a BBA in aviation administration from the University of North Dakota and a commercial helicopter license. Cory lives in Carmel, IN, with his wife and their two teenage daughters.

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