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Machine Learning Course Plan
Lecture One
Title: Introduction
Content:
Basic information about this course: books, TA, office, homework, project
and test form…
Introduce the definition of learning systems.
Give an overview of applications to show the goals of machine learning.
Introduce the aspects of developing a learning system: training data, concept
representation, function approximation.
Targets:
Understand the background of machine learning;
Remember the basic function of machine learning;
Get the general ideas of machine learning’s problem and point;
Processions:
What is Machine Learning?
Applications of ML
Disciplines relevant to ML
Well-Posed Learning Problems
Designing a Learning System
Perspectives and Issues In Machine Learning
How To Read This Book
Difficulties:
How to design a learning system;
The understand of concept.
Lecture Two
Title: Concept Learning and the General-to-Specific Ordering
Contents:
What is the concept learning task? Where is it applied to?
Make students understand concept learning is equivalent to search through a
hypothesis space.
Illustrate step by step the procedure of general-to-specific ordering of
hypotheses, to find the maximally specific hypotheses
Targets:
Understand the background of concept learning;
Remember the basic concept of concept learning, version space, etc;
Processions:
Introduction
A Concept Learning Task
Concept Learning as Search
Find-S:Finding a Maximally Specific Hypothesis
Difficulties:
What’s the process of concept learning;
Remember the concept of concept learning;
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