Introduction to Machine Learning with R

Rigorous Mathematical Analysis

Nonfiction, Computers, Advanced Computing, Programming, Data Modeling & Design, Database Management, Data Processing
Cover of the book Introduction to Machine Learning with R by Scott V. Burger, O'Reilly Media
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Scott V. Burger ISBN: 9781491976395
Publisher: O'Reilly Media Publication: March 7, 2018
Imprint: O'Reilly Media Language: English
Author: Scott V. Burger
ISBN: 9781491976395
Publisher: O'Reilly Media
Publication: March 7, 2018
Imprint: O'Reilly Media
Language: English

Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning principles. Using the R programming language, you’ll first start to learn with regression modelling and then move into more advanced topics such as neural networks and tree-based methods.

Finally, you’ll delve into the frontier of machine learning, using the caret package in R. Once you develop a familiarity with topics such as the difference between regression and classification models, you’ll be able to solve an array of machine learning problems. Author Scott V. Burger provides several examples to help you build a working knowledge of machine learning.

  • Explore machine learning models, algorithms, and data training
  • Understand machine learning algorithms for supervised and unsupervised cases
  • Examine statistical concepts for designing data for use in models
  • Dive into linear regression models used in business and science
  • Use single-layer and multilayer neural networks for calculating outcomes
  • Look at how tree-based models work, including popular decision trees
  • Get a comprehensive view of the machine learning ecosystem in R
  • Explore the powerhouse of tools available in R’s caret package
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning principles. Using the R programming language, you’ll first start to learn with regression modelling and then move into more advanced topics such as neural networks and tree-based methods.

Finally, you’ll delve into the frontier of machine learning, using the caret package in R. Once you develop a familiarity with topics such as the difference between regression and classification models, you’ll be able to solve an array of machine learning problems. Author Scott V. Burger provides several examples to help you build a working knowledge of machine learning.

More books from O'Reilly Media

Cover of the book Wikipedia: The Missing Manual by Scott V. Burger
Cover of the book Node.js for Embedded Systems by Scott V. Burger
Cover of the book Refactoring JavaScript by Scott V. Burger
Cover of the book Network Warrior by Scott V. Burger
Cover of the book Building Software Teams by Scott V. Burger
Cover of the book Publishing with iBooks Author by Scott V. Burger
Cover of the book Developing BlackBerry Tablet Applications with Flex 4.5 by Scott V. Burger
Cover of the book RESTful Web APIs by Scott V. Burger
Cover of the book Identity, Authentication, and Access Management in OpenStack by Scott V. Burger
Cover of the book REST in Practice by Scott V. Burger
Cover of the book Ajax on Rails by Scott V. Burger
Cover of the book Hadoop Application Architectures by Scott V. Burger
Cover of the book Excel Scientific and Engineering Cookbook by Scott V. Burger
Cover of the book Building Web Reputation Systems by Scott V. Burger
Cover of the book WordPress 4 komplett by Scott V. Burger
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy