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Neural Networks with R (Paperback)
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Neural Networks with R (Paperback)
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Uncover the power of artificial neural networks by implementing
them through R code. About This Book * Develop a strong background
in neural networks with R, to implement them in your applications *
Build smart systems using the power of deep learning * Real-world
case studies to illustrate the power of neural network models Who
This Book Is For This 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! What You Will
Learn * Set up R packages for neural networks and deep learning *
Understand the core concepts of artificial neural networks *
Understand neurons, perceptrons, bias, weights, and activation
functions * Implement supervised and unsupervised machine learning
in R for neural networks * Predict and classify data automatically
using neural networks * Evaluate and fine-tune the models you
build. In Detail 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. Style and approach A step-by-step guide filled with
real-world practical examples.
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