Machine learning using R : with time series and industry-based uses in R

Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use it to build a ML model from raw data. You will see how to use R programming with TensorFlow, thus avo...

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Bibliographic Details
Main Authors Ramasubramanian, Karthik (Author), Singh, Abhishek, 1976- (Author)
Format Electronic eBook
LanguageEnglish
Published [New York, New York] : Apress, [2019]
EditionSecond edition.
Subjects
Online AccessFull text
ISBN9781484242155
1484242157
9781484242148
1484242149
Physical Description1 online resource (xxiv, 700 pages)

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Summary:Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use it to build a ML model from raw data. You will see how to use R programming with TensorFlow, thus avoiding the effort of learning Python if you are only comfortable with R. As in the first edition, the authors have kept the fine balance of theory and application of machine learning through various real-world use-cases which gives you a comprehensive collection of topics in machine learning. New chapters in this edition cover time series models and deep learning. You will: Understand machine learning algorithms using R Master the process of building machine-learning models Cover the theoretical foundations of machine-learning algorithms See industry focused real-world use cases Tackle time series modeling in R Apply deep learning using Keras and TensorFlow in R.
ISBN:9781484242155
1484242157
9781484242148
1484242149
Access:Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty
Physical Description:1 online resource (xxiv, 700 pages)