Book Image

Neural Networks with R

By : Balaji Venkateswaran, Giuseppe Ciaburro
Book Image

Neural Networks with R

By: Balaji Venkateswaran, Giuseppe Ciaburro

Overview of this book

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.
Table of Contents (14 chapters)
Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Multilayer neural networks with neuralnet


After understanding the basics of deep learning, it's time to apply the skills acquired to a practical case. We've seen in the previous section that two libraries we know are listed in packages available in R for DNNs section. I refer to the nnet and neuralnet packages that we learned to use in the previous chapters through practical examples. Since we have some practice with the neuralnet library, I think we should start our practical exploration of the amazing world of deep learning from here.

To start, we introduce the dataset we will use to build and train the network. It is named the College dataset, and it contains statistics for a large number of US colleges, collected from the 1995 issue of US News and World Report. This dataset was taken from the StatLib library, which is maintained at Carnegie Mellon University, and was used in the ASA Section on Statistical Graphics.

Things for us are further simplified because we do not have to retrieve...