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Neural Networks with R

You're reading from   Neural Networks with R Build smart systems by implementing popular deep learning models in R

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781788397872
Length 270 pages
Edition 1st Edition
Languages
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Authors (2):
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Balaji Venkateswaran Balaji Venkateswaran
Author Profile Icon Balaji Venkateswaran
Balaji Venkateswaran
Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
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Toc

Table of Contents (8) Chapters Close

Preface 1. Neural Network and Artificial Intelligence Concepts 2. Learning Process in Neural Networks FREE CHAPTER 3. Deep Learning Using Multilayer Neural Networks 4. Perceptron Neural Network Modeling – Basic Models 5. Training and Visualizing a Neural Network in R 6. Recurrent and Convolutional Neural Networks 7. Use Cases of Neural Networks – Advanced Topics

Deep learning

DL forms an advanced neural network with numerous hidden layers. DL is a vast subject and is an important concept for building AI. It is used in various applications, such as:

  • Image recognition
  • Computer vision
  • Handwriting detection
  • Text classification
  • Multiclass classification
  • Regression problems, and more

We would see more about DL with R in the future chapters.

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