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tcsmath.github.io | ||
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blog.omega-prime.co.uk
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| | | | | The most fundamental technique in statistical learning is ordinary least squares (OLS) regression. If we have a vector of observations \(y\) and a matrix of features associated with each observation \(X\), then we assume the observations are a linear function of the features plus some (iid) random noise, \(\epsilon\): | |
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fa.bianp.net
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| | | | | Most proofs in optimization consist in using inequalities for a particular function class in some creative way. This is a cheatsheet with inequalities that I use most often. It considers class of functions that are convex, strongly convex and $L$-smooth. MathJax.Hub.Config({ extensions: ["tex2jax.js"], jax: ["input/TeX ... | |
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cgad.ski
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www.capicua.com
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| | | Machine Learning has gained traction over the last few years, cybersecurity being one of them. Let's learn how to use it to boost your system's protection! | ||
