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Applied Machine Learning Using mlr3 in R

Engelsk Paperback

Applied Machine Learning Using mlr3 in R

Engelsk Paperback
Tjek vores konkurrenters priser

mlr3 is an award-winning ecosystem of R packages that have been developed to enable state-of-the-art machine learning capabilities in R. Applied Machine Learning Using mlr3 in R gives an overview of flexible and robust machine learning methods, with an emphasis on how to implement them using mlr3 in R. It covers various key topics, including basic machine learning tasks, such as building and evaluating a predictive model; hyperparameter tuning of machine learning approaches to obtain peak performance; building machine learning pipelines that perform complex operations such as pre-processing followed by modelling followed by aggregation of predictions; and extending the mlr3 ecosystem with custom learners, measures, or pipeline components.

Features:

  • In-depth coverage of the mlr3 ecosystem for users and developers
  • Explanation and illustration of basic and advanced machine learning concepts
  • Ready to use code samples that can be adapted by the user for their application
  • Convenient and expressive machine learning pipelining enabling advanced modelling
  • Coverage of topics that are often ignored in other machine learning books

The book is primarily aimed at researchers, practitioners, and graduate students who use machine learning or who are interested in using it. It can be used as a textbook for an introductory or advanced machine learning class that uses R, as a reference for people who work with machine learning methods, and in industry for exploratory experiments in machine learning.

Tjek vores konkurrenters priser
Normalpris
kr 659
Fragt: 39 kr
6 - 8 hverdage
20 kr
Pakkegebyr
God 4 anmeldelser på
Tjek vores konkurrenters priser

mlr3 is an award-winning ecosystem of R packages that have been developed to enable state-of-the-art machine learning capabilities in R. Applied Machine Learning Using mlr3 in R gives an overview of flexible and robust machine learning methods, with an emphasis on how to implement them using mlr3 in R. It covers various key topics, including basic machine learning tasks, such as building and evaluating a predictive model; hyperparameter tuning of machine learning approaches to obtain peak performance; building machine learning pipelines that perform complex operations such as pre-processing followed by modelling followed by aggregation of predictions; and extending the mlr3 ecosystem with custom learners, measures, or pipeline components.

Features:

  • In-depth coverage of the mlr3 ecosystem for users and developers
  • Explanation and illustration of basic and advanced machine learning concepts
  • Ready to use code samples that can be adapted by the user for their application
  • Convenient and expressive machine learning pipelining enabling advanced modelling
  • Coverage of topics that are often ignored in other machine learning books

The book is primarily aimed at researchers, practitioners, and graduate students who use machine learning or who are interested in using it. It can be used as a textbook for an introductory or advanced machine learning class that uses R, as a reference for people who work with machine learning methods, and in industry for exploratory experiments in machine learning.

Produktdetaljer
Sprog: Engelsk
Sider: 340
ISBN-13: 9781032507545
Indbinding: Paperback
Udgave:
ISBN-10: 1032507543
Udg. Dato: 18 jan 2024
Længde: 20mm
Bredde: 252mm
Højde: 178mm
Forlag: Taylor & Francis Ltd
Oplagsdato: 18 jan 2024
Forfatter(e):
Forfatter(e)


Kategori Automatisk styrings- & reguleringsteknik


ISBN-13 9781032507545


Sprog Engelsk


Indbinding Paperback


Sider 340


Udgave


Længde 20mm


Bredde 252mm


Højde 178mm


Udg. Dato 18 jan 2024


Oplagsdato 18 jan 2024


Forlag Taylor & Francis Ltd