Neural networks are one of the most fascinating machine learning models for solving complex computational problems efficiently. Neural networks are used to solve a 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 the foundation to get started with advanced topics. The book begins with neural network design using the neuralnet package; then you'll build solid knowledge of how a neural network learns from data and the principles behind it. This book covers various types of neural networks, including recurrent neural networks and convoluted neural networks. You will not only learn how to train neural networks but 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 the practical examples in the book.