CS491/591 Introduction to Machine Learning Fall 2004

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CS491/591Introduction toMachine LearningFall
2004

• Terran Lane
• terran_at_cs.unm.edu

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Today

• Syllabus
• Q A
• Machine Learning the big picture

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Next time

• Pre-test (ungraded) -- 20 min
• Mostly to help me understand you
• Might brush up on linear algebra, basic
  probability, etc.
• Background and first learning algorithm

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Syllabus the crunchy stuff

• Textbook
• Resources
• Web page terran/classes/cs591-f04/
• Mailing list ml-class_at_cs.unm.edu
• Me terran_at_cs.unm.edu
• Office hours W, 900-1100 AM FEC345B
• Assignments/grading
• Homeworks
• Readings
• Exams
• Final Project undergrad grad
• Be on time
• Dont cheat

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What is Machine Learning?(what is learning at
all?)
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Topics in ML

• Supervised learning learning to identify and
  predict
• Classification/Concept learning
• Regression
• Unsupervised learning learning to group and
  describe
• Clustering
• Descriptive modeling
• Reinforcement learning learning to act and
  explore
• Markov decision processes
• Partial observability