Applied Artificial Intelligence
Applied Artificial Intelligence
An Engineering Approach
About the Book
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 machine learning, logic reasoning, natural language procesing and computer vision 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.
About the Author
Table of Contents
- Preface
- Copyright Notice
-
1. Introduction
- 1.1 Overview of this Book
- 1.2 What is AI?
- 1.3 A Brief History of AI
- 1.4 Impacts of AI on Society
- 1.5 Prominent AI Projects
- 1.6 Further Reading
- 1.7 Quick Check
-
2. Machine Learning
- 2.1 ML Applications
- 2.2 ML Areas and Tasks
- 2.3 ML Approaches
- 2.4 Example: Classifying Customers using Decision Tree Learning
- 2.5 ML Methodology
- 2.6 Automated Machine Learning
- 2.7 Services Maps and Product Maps
- 2.8 Engineering ML Applications
- 2.9 Quick Check
-
3. Knowledge Representation
- 3.1 Knowledge Graphs
- 3.2 Knowledge Representation Approaches
- 3.3 Semantic Web Standards
- 3.4 Querying knowledge graphs
- 3.5 Rule-based Reasoning
- 3.6 Knowledge Representation Services and Product Maps
- 3.7 Tips and Tricks
- 3.8 Quick Check
-
4. AI Application Architecture
- 4.1 AI Reference Architecture
- 4.2 Application Example: Virtual Museum Guide
- 4.3 Data Integration / Semantic Enrichment
- 4.4 Application Logic / Agents
- 4.5 Presentation
- 4.6 Programming Languages
- 4.7 Quick Check
-
5. Information Retrieval
- 5.1 Information Retrieval Services Map
- 5.2 Information Retrieval Product Map
- 5.3 Tips and Tricks
- 5.4 Application Example: Semantic Autosuggest Feature
- 5.5 Quick Check
-
6. Natural Language Processing
- 6.1 The Big Picture
- 6.2 Simple Approach: Bag-of-words Model
- 6.3 Deeper Semantic Analysis: From Letters to Sentences
- 6.4 Services and Product Maps
- 6.5 Examples
- 6.6 Quick Check
-
7. Computer Vision
- 7.1 Computer Vision Applications
- 7.2 Computer Vision Tasks and Approaches
- 7.3 Services and Product Maps
- 7.4 Examples
- 7.5 Quick Check
-
8. Complex Event Processing
- 8.1 Foundations
- 8.2 Application Example: Fault Detection in the Smart Factory
- 8.3 Services Map and Product Map
- 8.4 Quick Check
- 9. 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
- Notes
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