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bartwronski.com | ||
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algassert.com
Craig Gidney's computer science blog |
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www.jeremykun.com
The singular value decomposition (SVD) of a matrix is a fundamental tool in computer science, data analysis, and statistics. It's used for all kinds of applications from regression to prediction, to finding approximate solutions to optimization problems. In this series of two posts we'll motivate, define, compute, and use the singular value decomposition to analyze some data. (Jump to the second post) I want to spend the first post entirely on motivation and background. |
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mirawelner.com
A straightforward explanation of the spectroscopy work I did with sparse sensing at Purdue. |
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margint.blog
One discussion I find myself in more often recently is people asking me whether something is "really AI" or not. Often, what people seem to mean with that is whether someone is already using deep learning, or still "just" machine learning. I mentioned this to a friend in the industry and he just rolled his... |
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