Explore >> Select a destination
|
You are here 
|
www.aleksandrhovhannisyan.com | ||
| | | | |
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. | |
| | | | |
matthewmcateer.me
|
|
| | | | | Important mathematical prerequisites for getting into Machine Learning, Deep Learning, or any of the other space | |
| | | | |
hadrienj.github.io
|
|
| | | | | In this post, we will learn about the Moore Penrose pseudoinverse as a way to find an approaching solution where no solution exists. In some cases, a system ... | |
| | | | |
lucatrevisan.wordpress.com
|
|
| | | Welcome to phase two of in theory, in which we again talk about math. I spent last Fall teaching two courses and getting settled, I mostly traveled in January and February, and I have spent the last two months on my sofa catching up on TV series. Hence I will reach back to last Spring,... | ||
