Machine Learning/NBML/Linear Algebra: Difference between revisions
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=== Introduction === | |||
Linear algebra is fundamental to machine learning. The representation of data is typically embodied in vectors, and the transformations of that data in matricies. | |||
=== Resources === | |||
*Gilbert Strang has [http://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/video-lectures/ a set of video lectures] on the MIT Open Courseware page that are helpful: | |||
Revision as of 09:54, 6 January 2011
Introduction
Linear algebra is fundamental to machine learning. The representation of data is typically embodied in vectors, and the transformations of that data in matricies.
Resources
- Gilbert Strang has a set of video lectures on the MIT Open Courseware page that are helpful: