A compact introduction to Artificial Neural Networks (ANN) and deep learning. Learn how to implement Neural Networks in Python and to solve non linear problems such as the logic XOR function.
This book provides a compact and practical introduction into neural networks for people who know how to start and run Python programs.
The book shows in a step by step tutorial how neural networks are built, trained with sample data sets and how these networks are capable of solving non linear problems.
The goal of this book is to give the reader the ability to implement their own Neural Networks in Python and to apply this technique to any given problem. The simplicity of the tutorial as well as the simple syntax of the Python language quickly enables the reader to transfer that knowledge and algorithms to any other programming language of choice.
The book is explicitly NOT understood as a full introduction and compendium of AI in general as this would cover multiple thousands of pages for sure.
This book provides a compact and practical introduction into neural networks for people who know how to start and run Python programs.
The book shows in a step by step tutorial how neural networks are built, trained with sample data sets and how these networks are capable of solving non linear problems.
The goal of this book is to give the reader the ability to implement their own Neural Networks in Python and to apply this technique to any given problem. The simplicity of the tutorial as well as the simple syntax of the Python language quickly enables the reader to transfer that knowledge and algorithms to any other programming language of choice.
The book is explicitly NOT understood as a full introduction and compendium of AI in general as this would cover multiple thousands of pages for sure.
