Part I - AI Concepts
As the introductory section, this section will discuss the history and basic concepts of AI.
Chap 1 AI and Human Civilization - From Greek Mythology to AI Robotics
Chap 2 AI Fundamentals
2.1 Definition of AI
2.2 A Brief History of AI
2.3 Turing Test and AI
2.4 Strong AI vs Weak AI
2.5 Main components of AI
2.6 Case Study: Does Turing Test Really Work to Test for AI?
Part II - AI Technologies
This section discusses FIVE core AI Technologies which provide the building blocks of various different kind of AI applications, they are: Machine Learning (ML), Data Mining (DM), Computer Vision (CV), Natural Languages Processing (NLP), Ontology-based Search Engine (OSE).
Chap 3 Machine Learning (ML)
3.1 What is Machine Learning (ML)?
3.2 Supervised Learning (SL)
3.3 Unsupervised Learning (UL)
3.4 Reinforcement Learning (RL)
3.5 Case Study - How can we improve our memory by using Reinforcement Learning?
Chap 4 Data Mining (DM) & Big Data (BD)
4.1 What is Knowledge?
4.2 Data Mining, Big Data and Knowledge Discovery
4.3 Traditional Data Mining Technology
4.4 AI-based Data Mining Technology
4.5 Case Study - How to "mine" our purchase habit using Data Mining Technology?
Chap 5 Computer Vision (CV)
5.1 Computer Vision vs Human Vision
5.2 3 Levels of Computer Vision - Figure-ground Segmentation, Pattern Recognition, Active Vision
5.3 Active Vision and Robotics
5.4 Computer Vision Technology
5.5 Case Study - How AI-based Facial Recognition System works?
Chap 6 Natural Language Processing (NLP)
6.1 Human Language and Intelligence
6.2 Natural Language Processing in AI
6.3 Speech Recognition and Voice Synthesis
6.4 Machine Translation
6.5 Case Study - English Language Tutoring Robots
Chap 7 Ontological-based Search Engine (OSE)
7.1 Human Knowledge and Ontology
7.2 How Search Engine Works?
7.3 Traditional Search Engine vs. Ontological
About the Author:
Dr. Raymond Lee is the founder of Quantum Finance Forecast System QFFC, and currently an Associate Professor and IT Director at United International College (UIC). With more than 20 years of experience in IT consultancy and research into AI, Chaotic Neural Networks, Intelligent Fintech Systems, Quantum Finance, and Intelligent E-Commerce Systems, he has published over 100 publications and seven textbooks and research monographs on chaotic neural networks, AI-based fintech systems, intelligent agent technologies, chaotic cryptosystems, ontological agents, neural oscillators, biometrics, and weather simulation and forecasting systems. Dr. Lee's latest book, Quantum Finance: Intelligent Forecast and Trading Systems, published by Springer in Nov 2019, serves as a textbook for a new course on Quantum Finance at the UIC. He has successfully commercialized his AI fintech inventions in the business sectors in China and Hong Kong.
From 2012 to 2017, Dr. Lee served as Group CTO/Chief Analyst at Leanda Investment Group, China, where he applied his AI fintech invention - the Quantum Finance Forecast System - to major commodities in China for 1000+ investors. In Mar 2017, he set up the Quantum Finance Forecast Center (QFFC, http: //qffc.org), a non-profit, AI fintech R&D and worldwide financial forecast center where traders and individual investors around the globe can access (free of charge) 129 financial forecasts based on the latest AI, chaotic neural network and quantum field theory technologies. QFFC currently has over 10,000 registered members, which include professional traders, quants, and independent investors from major funding houses and financial institutions.
