Explore >> Select a destination
|
You are here 
|
antoinevastel.com | ||
| | | | |
fa.bianp.net
|
|
| | | | | A naive implementation of the logistic regression loss can results in numerical indeterminacy even for moderate values. This post takes a closer look into the source of these instabilities and discusses more robust Python implementations. hljs.initHighlightingOnLoad(); MathJax.Hub.Config({ extensions: ["tex2jax.js"], jax: ["input/TeX", "output/HTML-CSS"], tex2jax: { inlineMath ... | |
| | | | |
nhigham.com
|
|
| | | | | The pseudoinverse is an extension of the concept of the inverse of a nonsingular square matrix to singular matrices and rectangular matrices. It is one of many generalized inverses, but the one most useful in practice as it has a number of special properties. The pseudoinverse of a matrix $latex A\in\mathbb{C}^{m\times n}$ is an $latex... | |
| | | | |
yoursite.com
|
|
| | | | | ??????NumPy??????????????Jay Mody????????????????????????????????????NumPy????????????? ?????Computing Distance Matrices with NumPy ?????? (????????) | |
| | | | |
www.jeremykun.com
|
|
| | | This post is mainly mathematical. We left it out of our introduction to categories for brevity, but we should lay these definitions down and some examples before continuing on to universal properties and doing more computation. The reader should feel free to skip this post and return to it later when the words "isomorphism," "monomorphism," and "epimorphism" come up again. Perhaps the most important part of this post is the description of an isomorphism. | ||
