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Neural networks with R: smart models using CNN, RNN, deep learning, and artificial intelligence principles

By: Contributor(s): Material type: TextTextPublication details: Packt Publishing 2017 BriminghamDescription: iv, 256 pISBN:
  • 9781788397872
Subject(s): DDC classification:
  • C4N3 004.56
Summary: Neural networks are one of the most fascinating machine learning models for solving complex computational problems efficiently. Neural networks are used to solve wide range of problems in different areas of AI and machine learning. This book explains the niche aspects of neural networking and provides you with foundation to get started with advanced topics. The book begins with neural network design using the neural net package, then you’ll build a solid foundation knowledge of how a neural network learns from data, and the principles behind it. This book covers various types of neural network including recurrent neural networks and convoluted neural networks. You will not only learn how to train neural networks, but will also explore generalization of these networks. Later we will delve into combining different neural network models and work with the real-world use cases. By the end of this book, you will learn to implement neural network models in your applications with the help of practical examples in the book https://www.packtpub.com/big-data-and-business-intelligence/neural-networks-r
List(s) this item appears in: Artificial Intelligence (AI) | Artificial intelligence
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Item type Current library Item location Collection Shelving location Call number Status Date due Barcode
Books Vikram Sarabhai Library Rack 2-A / Slot 31 (0 Floor, West Wing) Non-fiction General Stacks 004.56 C4N3 (Browse shelf(Opens below)) Available 195683

Neural networks are one of the most fascinating machine learning models for solving complex computational problems efficiently. Neural networks are used to solve wide range of problems in different areas of AI and machine learning.

This book explains the niche aspects of neural networking and provides you with foundation to get started with advanced topics. The book begins with neural network design using the neural net package, then you’ll build a solid foundation knowledge of how a neural network learns from data, and the principles behind it. This book covers various types of neural network including recurrent neural networks and convoluted neural networks. You will not only learn how to train neural networks, but will also explore generalization of these networks. Later we will delve into combining different neural network models and work with the real-world use cases.

By the end of this book, you will learn to implement neural network models in your applications with the help of practical examples in the book


https://www.packtpub.com/big-data-and-business-intelligence/neural-networks-r

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