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Idioma: Inglés
Publicado por Manning Publications, New York, 2020
ISBN 10: 1617296570 ISBN 13: 9781617296574
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Añadir al carritoPaperback. Condición: new. Paperback. Machine Learning with R, tidyverse, and mlr teaches readers how to gain valuable insights from their data using the powerful R programming language. In his engaging and informal style, author and R expert Hefin Ioan Rhys lays a firm foundation of ML basics and introduces readers to the tidyverse, a powerful set of R tools designed specifically for practical data science. Key Features Commonly used ML techniques Using the tidyverse packages to organize and plot your data Validating model performance Choosing the best ML model for your task A variety of hands-on coding exercises ML best practices For readers with basic programming skills in R, Python, or another standard programming language. About the technology Machine learning techniques accurately and efficiently identify patterns and relationships in data and use those models to make predictions about new data. ML techniques can work on even relatively small datasets, making these skills a powerful ally for nearly any data analysis task. Hefin Ioan Rhysis a senior laboratory research scientist in the Flow Cytometry Shared Technology Platform at The Francis Crick Institute. He spent the final year of his PhD program teaching basic R skills at the university. A data science and machine learning enthusiast, he has his own Youtube channel featuring screencast tutorials in R and R Studio. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Añadir al carritopaperback. Condición: Gut. 511 Seiten; 9781617296574.3 Gewicht in Gramm: 1.
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Añadir al carritoCondición: New. Über den AutorHefin Ioan Rhysis a senior laboratory research scientist in the Flow Cytometry Shared Technology Platform at The Francis Crick Institute. He spent the final year of his PhD program teaching basic R skills at the uni.
Idioma: Inglés
Publicado por Manning Publications, New York, 2020
ISBN 10: 1617296570 ISBN 13: 9781617296574
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 115,73
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Añadir al carritoPaperback. Condición: new. Paperback. Machine Learning with R, tidyverse, and mlr teaches readers how to gain valuable insights from their data using the powerful R programming language. In his engaging and informal style, author and R expert Hefin Ioan Rhys lays a firm foundation of ML basics and introduces readers to the tidyverse, a powerful set of R tools designed specifically for practical data science. Key Features Commonly used ML techniques Using the tidyverse packages to organize and plot your data Validating model performance Choosing the best ML model for your task A variety of hands-on coding exercises ML best practices For readers with basic programming skills in R, Python, or another standard programming language. About the technology Machine learning techniques accurately and efficiently identify patterns and relationships in data and use those models to make predictions about new data. ML techniques can work on even relatively small datasets, making these skills a powerful ally for nearly any data analysis task. Hefin Ioan Rhysis a senior laboratory research scientist in the Flow Cytometry Shared Technology Platform at The Francis Crick Institute. He spent the final year of his PhD program teaching basic R skills at the university. A data science and machine learning enthusiast, he has his own Youtube channel featuring screencast tutorials in R and R Studio. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Idioma: Chino
Publicado por Tsinghua University Press, 2021
ISBN 10: 7302578273 ISBN 13: 9787302578277
Librería: liu xing, Nanjing, JS, China
EUR 132,04
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Añadir al carritopaperback. Condición: New. Paperback. Pub Date: 2021-06-01 Pages: 396 Publisher: Tsinghua University Press Machine Learning Practical Use R. Tidyverse. and mlr will start your machine learning journey using RStudio and the awesome mlr package.?This practical guide simplifies the theory and avoids unnecessary complex statistics and mathematics. All core machine learning techniques are clearly explained through graphics and easy-to-master examples.?The content of each chapter is very fascinating. You will master how to p.