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 hadrienj.github.io
Introduction to The Moore Penrose Pseudoinverse using Python/Numpy examples and drawings
| | blog.georgeshakan.com
Singular Value Decomposition and PCA | George Shakan
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| | Principal Component Analysis (PCA) is a popular technique in machine learning for dimension reduction. It can be derived from Singular Value Decomposition (SVD) which we will discuss in this post. We will cover the math, an example in python, and finally some intuition. The Math SVD asserts that any $latex m \times d$ matrix $latex...
| | vxy10.github.io
Least-square fitting using matrix derivatives
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| | Course material for MEC 560: Advanced Control Systems taught at Stony Brook University by Dr. Vivek Yadav
| | robotchinwag.com
Gradients of Matrix Multiplication in Deep Learning | Robot Chinwag
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| | Deriving the gradients for the backward pass for matrix multiplication using tensor calculus
| | nikita-volkov.github.io
Internal convention is a mistake - Functional programming debugs you
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| In this post I'm gonna highlight the issues of the "Internal" modularisation convention and provide a proper solution to the same set of problems.