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CS 59000: Statistical Machine Learning - Lecture 1 by Alan Qi, Fall 2008 - Prof. Yuan Qi, Study notes of Computer Science
The first lecture slides for cs 59000: statistical machine learning course offered by alan qi at purdue university in fall 2008. The lecture covers the importance of machine learning, applications, and logistics of the course. Students will learn about various topics such as probability distributions, linear regression, bayesian networks, and kernel methods. Prerequisites include calculus, linear algebra, and probability.
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Download CS 59000: Statistical Machine Learning - Lecture 1 by Alan Qi, Fall 2008 - Prof. Yuan Qi and more Study notes Computer Science in PDF only on Docsity! CS 59000 Statistical Machine learning
Lecture 1
Why take machine learning Solve problems in computer vision, natural language processing, systems biology, social network analysis, finance, etc. Research in machine learning Find industrial opportunities Other reasons (enjoying learning elegant theories, doing fun/practical projects ?)
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Logistics Time: TR 10:30 am ‐ 11:45 am Instructor: Alan Qi Lawson 1207 • alanqi[at]cs.purdue.edu Teaching assistant: Yao Zhu Lawson B116F • zhu36[at]cs.purdue.edu Office hours: MW 2:00 pm ‐ 3:15 pm or by appointment Web page: http://www.cs.purdue.edu/~alanqi/Courses/CS59000.html Workload Homework: 5 to 8 assignments Midterm in mid October Review of recent research Students will choose a subtopic of machine learning research, select three recent conference papers on the topic, and write a 2 page report outlining the main ideas of papers and relate them to the context of the course. Workload (cont.): Final project • Topic: Anything that is clearly pertains to the course material. • Pre‐report: One‐page paragraph description of your project a month before the project is due. • Collaboration: You are encouraged to collaborate on the project. We expect a four page write‐up about the project, which should clearly and succintly describe the project goal, methods, and your results. Each group should submit only one copy of the write‐up and include all the names of the group members (a two person group will have 6 pages, a three person group will have 8 pages, and so on). Grading
* Class participation: 10%
« Homework: 30%
Assignments will be accepted up to 5 days late with a
penalty of 10% per day. No assignment will be accepted
more than 5 days late.
« Midterm: 25%
¢ Paper Review: 10%
¢ Final project: 25%
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