Pages tagged

http://www.starling-software.com/employment/programmer-competency-matrix.html

http://www.starling-software.com/employment/programmer-competency-matrix.html

equentlyProgrammer Competency Matrix | IndianGeek

http://www.indiangeek.net/programmer-competency-matrix/

Basic sorting, searching and data structure traversal and retrieval algorithms

pretty coolSingular Value Decomposition

http://www.uwlax.edu/faculty/will/svd/index.html

."Main Page - Eigen

http://eigen.tuxfamily.org/index.php?title=Main_Page

Overview Eigen is a C++ template library for linear algebra: vectors, matrices, and related algorithms. It is: * Versatile. (See modules and tutorial). Eigen handles, without code duplication, and in a completely integrated way: o both fixed-size and dynamic-size matrices and vectors. o both dense and sparse (the latter is still experimental) matrices and vectors. o both plain matrices/vectors and abstract expressions. o both column-major (the default) and row-major matrix storage. o both basic matrix/vector manipulation and many more advanced, specialized modules providing algorithms for linear algebra, geometry, quaternions, or advanced array manipulation. * Fast. (See benchmark). o Expression templates allow to intelligently remove temporaries and enable lazy evaluation, when that is appropriate -- Eigen takes care of this automatically and handles aliasing too in most cases. o Explicit vectorization is

Main Page - Eigen

Eigen 2 is a C++ template library for linear algebra: vectors, matrices, and related algorithms.The Twitter Approval Matrix -- New York Magazine

http://nymag.com/arts/all/approvalmatrix/56103/

RT @AudioJungle: The Twitter Approval Matrix http://bit.ly/d3lqj

An infographic showing the best and worst Twitterers

Horifically unfunny, but the fact it includes Kurt Andersen makes it a black hole of irony http://tinyurl.com/cgrdda (via @eliztesch)

"Our deliberately oversimplified guide to whose tweets are worth following."

Our deliberately oversimplified guide to whose tweets are worth following.Feature Column from the AMS

http://www.ams.org/featurecolumn/archive/svd.html

An intuitive explanation of the geometric meaning behind SVD.

Good explanation of the SVD

Geometric interpretation of SVD.JavaScript Framework Matrix - Overview with functions and examples

http://matthiasschuetz.com/javascript-framework-matrix/en/

The JavaScript Framework Matrix shall give you an overview of popular JavaScript frameworks and their functions. There are various examples for the frameworks and every snippet contains links to the official documentation. The choice of a framework depends on many factors and can't be made of this document only. The matrix shall solely demonstrate the different API styles and functionalities of the JavaScript libraries.Netflix prize tribute: Recommendation algorithm in Python | This Number Crunching Life

http://blog.smellthedata.com/2009/06/netflix-prize-tribute-recommendation.html

Quick implementation of the Netflix recommendation algorithm (probablistic matrix factorization) in Python.

probabalistic matrix factorisation

I test my code using synthetic data, where I first make up latent vectors for users and items, then I generate some training set ratings by multiplying some latent user vectors by latent item vectors then adding some noise. I then discard the latent vectors and just give the model the synthetic ratings.Матрица компетентности программиста - Google Docs

http://spreadsheets.google.com/pub?key=pmAWNZu8sBj_tXy5ms5foVQ

часть 2: http://docs.google.com/View?docid=d28gm4q_56hmv6f72zxkcd - A Webcomic - Matrix Revisited

http://xkcd.com/566/

too bad they never made any sequels

xkcd - A Webcomic - #566: Matrix Revisited