Applied Artificial Intelligence: An Engineering Approach

✍ Scribed by Bernhard G Humm

• Publisher: Bernhard G Humm
• Year: 2022
• Tongue: English
• Leaves: 165
• Edition: 2
• Category: Library

✦ Synopsis

Why yet another book on Artificial Intelligence? It is true that hundreds of publications on Artificial Intelligence (AI) have been published within the last decades - scientific papers and text books. Most of them focus on the theory behind AI solutions: logic, reasoning, statistical foundations, etc. However, little can be found on engineering AI applications.Modern, complex IT applications are not built from scratch but by integrating off-the-shelf components: libraries, frameworks, and services. The same applies, of course, for AI applications. Over the last decades, numerous off-the-shelf components for AI base functionality such as logic, reasoning, and statistics have been implemented - commercial and open source. Integrating such components into user friendly, high-performance, and maintainable AI applications requires specific engineering skills. "Applied Artificial Intelligence - An Engingeering Approach" focuses on those skills.

✦ Table of Contents

Table of Contents
Preface
Copyright Notice
Introduction
Overview of this Book
What is AI?
A Brief History of AI
Impacts of AI on Society
Prominent AI Projects
Further Reading
Quick Check
Machine Learning
ML Applications
ML Areas and Tasks
ML Approaches
Example: Classifying Customers using Decision Tree Learning
ML Methodology
Automated Machine Learning
Services Maps and Product Maps
Engineering ML Applications
Quick Check
Knowledge Representation
Knowledge Graphs
Knowledge Representation Approaches
Semantic Web Standards
Querying knowledge graphs
Rule-based Reasoning
Knowledge Representation Services and Product Maps
Tips and Tricks
Quick Check
AI Application Architecture
AI Reference Architecture
Application Example: Virtual Museum Guide
Data Integration / Semantic Enrichment
Application Logic / Agents
Presentation
Programming Languages
Quick Check
Information Retrieval
Information Retrieval Services Map
Information Retrieval Product Map
Tips and Tricks
Application Example: Semantic Autosuggest Feature
Quick Check
Natural Language Processing
The Big Picture
Simple Approach: Bag-of-words Model
Deeper Semantic Analysis: From Letters to Sentences
Services and Product Maps
Examples
Quick Check
Computer Vision
Computer Vision Applications
Computer Vision Tasks and Approaches
Services and Product Maps
Examples
Quick Check
Complex Event Processing
Foundations
Application Example: Fault Detection in the Smart Factory
Services Map and Product Map
Quick Check
Conclusions
Literature
Appendix: Product Tables
Machine Learning
Knowledge Representation
AI Application Architecture
Agent Frameworks
Information Retrieval
Natural Language Processing
Computer Vision
Complex Event Processing
About the Author