Explanation Based Learning
この電子書籍について
A type of machine learning known as explanation-based learning, or EBL for short, takes advantage of an extremely robust, or even flawless, domain theory in order to generalize from training data or construct concepts. It also has a connection with encoding, or memory, which assists with learning.
How You Will Benefit
(I) Insights, and validations about the following topics:
Chapter 1: Explanation-based learning
Chapter 2: Computational linguistics
Chapter 3: Natural language processing
Chapter 4: Corpus linguistics
Chapter 5: Parsing
Chapter 6: Question answering
Chapter 7: Link grammar
Chapter 8: Grammar induction
Chapter 9: Structured prediction
Chapter 10: Deep linguistic processing
(II) Answering the public top questions about explanation based learning.
(III) Real world examples for the usage of explanation based learning in many fields.
(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of explanation based learning' technologies.
Who This Book Is For
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of explanation based learning.
