Hands-On Machine Learning With R
Brad Boehmke
From Basi6 International, Irving, TX, U.S.A.
Seller rating 5 out of 5 stars
AbeBooks Seller since 24 June 2016
New - Hardcover
Quantity: 4 available
Add to basketFrom Basi6 International, Irving, TX, U.S.A.
Seller rating 5 out of 5 stars
AbeBooks Seller since 24 June 2016
Quantity: 4 available
Add to basketAbout this Item
New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Seller Inventory # ABEJUNE24-157458
Bibliographic Details
Title: Hands-On Machine Learning With R
Publisher: Chapman and Hall/CRC
Publication Date: 2019
Binding: Hardcover
Condition: Brand New
About this title
Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory.
Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R’s machine learning stack and be able to implement a systematic approach for producing high quality modeling results.
Features:
· Offers a practical and applied introduction to the most popular machine learning methods.
· Topics covered include feature engineering, resampling, deep learning and more.
· Uses a hands-on approach and real world data.
"Hands-On Machine Learning with R is a great resource for understanding and applying models. Each section provides descriptions and instructions using a wide range of R packages."
- Max Kuhn, Machine Learning Software Engineer, RStudio
"You can't find a better overview of practical machine learning methods implemented with R."
- JD Long, co-author of R Cookbook
"Simultaneously approachable, accessible, and rigorous, Hands-On Machine Learning with R offers a balance of theory and implementation that can actually bring you from relative novice to competent practitioner."
- Mara Averick, RStudio Dev Advocate
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