Difference between revisions of "CMSC422 - Introduction to Machine Learning"
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| − | { | + | '''Course Information''' <br> |
| + | Machine Learning studies representations and algorithms that allow machines to improve their performance on a task from experience. This is a broad overview of existing methods for machine learning and an introduction to adaptive systems in general. Emphasis is given to practical aspects of machine learning and data mining. | ||
| + | |||
| + | {| style="text-align:left; width: 550PX;" | ||
| + | ! Instructor | ||
| + | ! Section | ||
| + | ! Day & Time | ||
| + | ! Location | ||
| + | |- style="vertical-align:top;" | | ||
| + | | James Reggia || style="vertical-align:top;" | 0101 || TuTh 12:30pm - 1:45pm || style="vertical-align:top;" | [http://maps.umd.edu/map/index.html?Welcome=False&MapView=Detailed&LocationType=Building&LocationName=406 CSI 2117]<br> | ||
| + | |- style="vertical-align:top;" | | ||
| + | | David Jacobs || style="vertical-align:top;" | 0201 || MW 2:00pm - 3:15pm || style="vertical-align:top;" | [http://maps.umd.edu/map/index.html?Welcome=False&MapView=Detailed&LocationType=Building&LocationName=406 CSI 2117] | ||
| + | |} | ||
| + | |||
| + | ''' Course Prerequisite(s) ''' <br> | ||
| + | Prerequisite: Minimum grade of C- in CMSC351 and CMSC330; and permission of CMNS-Computer Science department. Recommended: STAT400. | ||
| + | |||
| + | ''' Class Webpage ''' <br> | ||
| + | |||
| + | ''' Hours Per Week ''' <br> | ||
| + | |||
| + | ''' Languages Used ''' <br> | ||
| + | |||
| + | |||
| + | ''' Recommended Prior Experience ''' <br> | ||
| + | |||
| + | ''' Projects, Exams, or other Assessments ''' <br> | ||
| + | |||
| + | ''' Misc Info ''' <br> | ||
Latest revision as of 19:56, 4 April 2017
Course Information
Machine Learning studies representations and algorithms that allow machines to improve their performance on a task from experience. This is a broad overview of existing methods for machine learning and an introduction to adaptive systems in general. Emphasis is given to practical aspects of machine learning and data mining.
| Instructor | Section | Day & Time | Location |
|---|---|---|---|
| James Reggia | 0101 | TuTh 12:30pm - 1:45pm | CSI 2117 |
| David Jacobs | 0201 | MW 2:00pm - 3:15pm | CSI 2117 |
Course Prerequisite(s)
Prerequisite: Minimum grade of C- in CMSC351 and CMSC330; and permission of CMNS-Computer Science department. Recommended: STAT400.
Class Webpage
Hours Per Week
Languages Used
Recommended Prior Experience
Projects, Exams, or other Assessments
Misc Info
