Course offered Spring term 2004.
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Location: |
Tuesday and Thursday |
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Instructor: |
Professor |
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Office: |
ECOT 525 |
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Office Hours: |
Tuesday and Wednesday |
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Phone: |
303-492-4419 |
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Email: |
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Course URL: |
How does an internet vender know which consumer group or individual to target for advertising? How do we find all pictures of Arnold Schwarzenegger in a large image database? Which gene is responsible for the cancer that runs in my family? Machine learning algorithms are at the heart of many computer applications designed to address these types of questions. Other important applications include Data Mining, Robotics, Profiling, User Interfaces, Document Characterization, Bioinformatics, and Linguistics.
Machine learning is the study of building systems that learn from experience. Machine learning algorithms are designed to address problem domains where good theoretical models don’t exist, but where empirical observations can be made.
This course covers the three main subfields of machine learning: supervised, unsupervised and reinforcement learning. Emphasis is placed on a practical and theoretical understanding of the most widely applicable algorithms and their applications.
Course Textbook: Artificial Intelligence: A Modern Approach, by Stuart Russell and Peter Norvig
Grading:
Project 60%
Class Participation 10%
Final 30%
Disability Accommodations
If you qualify for accommodations because of a disability, please submit to me a letter from Disability Services in a timely manner so that your needs may be addressed. Disability Services determines accommodations based on documented disabilities. (303-492-8671, Willard 322, http://www.colorado.edu/disabilityservices).
Religious Accommodations
If you feel you can't be present at the final for religious reasons, please contact me as soon as possible to make arrangements.
Honor Code
The campus has adopted an Honor Code. It includes the following pledge which will be placed on all your exams and you will need to include on your assignments:
On my honor, as a
Except when I specify otherwise, the assignments in this class will be done individually. You may discuss the assignments with one another but the final product (program, paper, etc) must be yours alone.