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Machine Learning Using R

With Time Series and Industry-Based Use Cases in R

Karthik Ramasubramanian, Abhishek Singh
Livre broché | Anglais
93,95 €
+ 187 points
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Description

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.

What You'll Learn

  • 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

Who This Book is For

Data scientists, data science professionals, and researchers in academia who want to understand the nuances of machine-learning approaches/algorithms in practice using R.

Spécifications

Parties prenantes

Auteur(s) :
Editeur:

Contenu

Nombre de pages :
700
Langue:
Anglais

Caractéristiques

EAN:
9781484242148
Date de parution :
13-12-18
Format:
Livre broché
Format numérique:
Trade paperback (VS)
Dimensions :
178 mm x 254 mm
Poids :
1238 g

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