Neural Networks with R: Smart models using CNN, RNN, deep learning, and artificial intelligence principles - Info and Reading Options
By Giuseppe Ciaburro and Balaji Venkateswaran

"Neural Networks with R: Smart models using CNN, RNN, deep learning, and artificial intelligence principles" is published by Packt Publishing - ebooks Account in Sep 27, 2017 - Birmingham and it has 270 pages.
“Neural Networks with R: Smart models using CNN, RNN, deep learning, and artificial intelligence principles” Metadata:
- Title: ➤ Neural Networks with R: Smart models using CNN, RNN, deep learning, and artificial intelligence principles
- Authors: Giuseppe CiaburroBalaji Venkateswaran
- Number of Pages: 270
- Publisher: ➤ Packt Publishing - ebooks Account
- Publish Date: Sep 27, 2017
- Publish Location: Birmingham
“Neural Networks with R: Smart models using CNN, RNN, deep learning, and artificial intelligence principles” Subjects and Themes:
- Subjects: ➤ Neural networks (computer science) - R (Computer program language) - Neural networks (Computer science) - Machine learning - Artificial intelligence - COMPUTERS - Neural Networks - Intelligence (AI) & Semantics - Information Technology - COMPUTERS / General - Neural circuitry
Edition Identifiers:
- The Open Library ID: OL26834237M - OL19543551W
- Online Computer Library Center (OCLC) ID: 1008968699 - 1005542213
- ISBN-13: 9781788397872 - 9781788399418
- ISBN-10: 1788397878
- All ISBNs: 1788397878 - 9781788397872 - 9781788399418
AI-generated Review of “Neural Networks with R: Smart models using CNN, RNN, deep learning, and artificial intelligence principles”:
"Neural Networks with R: Smart models using CNN, RNN, deep learning, and artificial intelligence principles" Description:
Open Data:
bUncover the power of artificial neural networks by implementing them through R code./bh2About This Book/h2ulliDevelop a strong background in neural networks with R, to implement them in your applications/liliBuild smart systems using the power of deep learning/liliReal-world case studies to illustrate the power of neural network models/li/ulh2Who This Book Is For/h2This book is intended for anyone who has a statistical background with knowledge in R and wants to work with neural networks to get better results from complex data. If you are interested in artificial intelligence and deep learning and you want to level up, then this book is what you need!h2What You Will Learn/h2ulliSet up R packages for neural networks and deep learning/liliUnderstand the core concepts of artificial neural networks/liliUnderstand neurons, perceptrons, bias, weights, and activation functions/liliImplement supervised and unsupervised machine learning in R for neural networks/liliPredict and classify data automatically using neural networks/liliEvaluate and fine-tune the models you build./li/ulh2In Detail/h2Neural 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.h2Style and approach/h2A step-by-step guide filled with real-world practical examples
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