Delphi Cookbook - Third Edition : Recipes to master Delphi for IoT integrations, cross-platform, mobile and server-side development

Daniele Spinetti

ISBN 10: 1788621301 / ISBN 13: 9781788621304

Published by Packt Publishing, 2018

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - Uncover the power of artificial neural networks by implementing them through R code. Key Features 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 Book Description 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. 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. 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!

Seller Inventory # 9781788621304

Bibliographic Details

• Title: Delphi Cookbook - Third Edition : Recipes to master Delphi for IoT integrations, cross-platform, mobile and server-side development
• Publisher: Packt Publishing
• Publication Date: 2018
• Language: English
• ISBN 10: 1788621301
• ISBN 13: 9781788621304
• Binding: Taschenbuch
• Edition: 3rd Edition
• Condition: Neu

About this title

Synopsis

Uncover the power of artificial neural networks by implementing them through R code.

Key Features

• 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

Book Description

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.

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.

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!

About the Author

Daniele Spinetti is a software architect living in Rome. He is an Embarcadero MVP. Delphi/Object Pascal is his favorite tool/programming language, and he is a lead and active member of several projects in the open source community. In his tutoring activities (conferences and training), he likes to talk about innovative topics in software architectures. He's a huge fan of design patterns and TDD.

Daniele Teti is a software architect, trainer, and consultant with over 20 years of experience. He drives the development of the most popular Delphi open source project on GitHub-DelphiMVCFramework. He's also a huge fan of design patterns, machine learning, and AI. Daniele is the CEO of BIT Time Professionals, an Italian company specializing in high-level consultancy, training, development, and machine learning systems.