E-book details

Machine Learning with R. Learn techniques for building and improving machine learning models, from data preparation to model tuning, evaluation, and working with big data - Fourth Edition

Machine Learning with R. Learn techniques for building and improving machine learning models, from data preparation to model tuning, evaluation, and working with big data - Fourth Edition

Brett Lantz

Ebook
Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data.

Machine Learning with R, Fourth Edition, provides a hands-on, accessible, and readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to know for data pre-processing, uncovering key insights, making new predictions, and visualizing your findings. This 10th Anniversary Edition features several new chapters that reflect the progress of machine learning in the last few years and help you build your data science skills and tackle more challenging problems, including making successful machine learning models and advanced data preparation, building better learners, and making use of big data.

You'll also find this classic R data science book updated to R 4.0.0 with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Whether you're looking to take your first steps with R for machine learning or making sure your skills and knowledge are up to date, this is an unmissable read that will help you find powerful new insights in your data.
  • 1. Introducing Machine Learning
  • 2. Managing and Understanding Data
  • 3. Lazy Learning – Classification Using Nearest Neighbors
  • 4. Probabilistic Learning – Classification Using Naive Bayes
  • 5. Divide and Conquer – Classification Using Decision Trees and Rules
  • 6. Forecasting Numeric Data – Regression Methods
  • 7. Black-Box Methods – Neural Networks and Support Vector Machines
  • 8. Finding Patterns – Market Basket Analysis Using Association Rules
  • 9. Finding Groups of Data – Clustering with k-means
  • 10. Evaluating Model Performance
  • 11. Being Successful with Machine Learning
  • 12. Advanced Data Preparation
  • 13. Challenging Data – Too Much, Too Little, Too Complex
  • 14. Building Better Learners
  • 15. Making Use of Big Data
  • Title: Machine Learning with R. Learn techniques for building and improving machine learning models, from data preparation to model tuning, evaluation, and working with big data - Fourth Edition
  • Author: Brett Lantz
  • Original title: Machine Learning with R. Learn techniques for building and improving machine learning models, from data preparation to model tuning, evaluation, and working with big data - Fourth Edition
  • ISBN: 9781801076050, 9781801076050
  • Date of issue: 2023-05-29
  • Format: Ebook
  • Item ID: e_3d3u
  • Publisher: Packt Publishing