Applications of Linear Algebra (Part 2)
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Our world is in a data deluge with ever increasing sizes of datasets. Linear algebra is a tool to manage and analyze such data.
This course is part 2 of a 2-part course, with this part extending smoothly from the first. Note, however, that part 1, is not a prerequisite for part 2. In this part of the course, we'll develop the linear algebra more fully than part 1. This class has a focus on data mining with some applications of computer graphics. We'll discuss, in further depth than part 1, sports ranking and ways to rate teams from thousands of games. We’ll apply the methods to March Madness. We'll also learn methods behind web search, utilized by such companies as Google. We'll also learn to cluster data to find similar groups and also how to compress images to lower the amount of storage used to store them. The tools that we learn can be applied to applications of your interest. For instance, clustering data to find similar movies can be applied to find similar songs or friends. So, come to this course ready to investigate your own ideas.
Courses offered via edX.org are not eligible for academic credit from Davidson College. A passing score in a DavidsonX course(s) will only be eligible for a verified certificate generated by edX.org.
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Rating | Not enough ratings |
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Length | 4 weeks |
Effort | 12 - 18 hours per week |
Starts | Apr 6 (473 weeks ago) |
Cost | $0 |
From | Davidson College, DavidsonX via edX |
Instructors | Tim Chartier, Allison Dulin, Kristen Eshleman, Robert McSwain, Sara Swanson |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Programming Data Science Mathematics |
Tags | Computer Science Data Analysis & Statistics Math |
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Rating | Not enough ratings |
---|---|
Length | 4 weeks |
Effort | 12 - 18 hours per week |
Starts | Apr 6 (473 weeks ago) |
Cost | $0 |
From | Davidson College, DavidsonX via edX |
Instructors | Tim Chartier, Allison Dulin, Kristen Eshleman, Robert McSwain, Sara Swanson |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Programming Data Science Mathematics |
Tags | Computer Science Data Analysis & Statistics Math |
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