Links and Resources

Statistics

• Simple Statistics: descriptive statistics, bayesian classifier, distribution, linear regression. http://simplestatistics.org/

• jstat: matrix, vector operations, statistics functions, distribution, linear algebra, regression, statistical tests.

• science.js: scientific and statistical computing. https://github.com/jasondavies/science.js/

• numeric.js: sophisticated numerical computations for JavaScript. http://www.numericjs.com/

• big.js: arbitrary-precision decimal arithmetic. https://github.com/MikeMcl/big.js/

• sylvester.js: vector and matrix operations. https://github.com/jcoglan/sylvester

• linearReg.js: linear regression. https://github.com/lastlegion/linearReg.js

Machine Learning

• Encog's machine learning: Bayesian Networks, Hidden Markov Models and Support Vector Machines. https://github.com/encog/encog-javascript

• ConvNetJS: deep learning. http://cs.stanford.edu/people/karpathy/convnetjs/

• brain.js: neural network. https://github.com/harthur/brain

• svm.js: support vector machine. https://github.com/karpathy/svmjs

• forest.js: random forest. https://github.com/karpathy/forestjs

Data Handling

• datalib: data loading, type inference, common statistics, and string templates. https://vega.github.io/datalib/

• d3-array: array manipulation (d3.js module) https://github.com/d3/d3-array

Data Algorithms

• clusterfck.js: k-mean clustering https://github.com/harthur/clusterfck

• density-clustering: dbscan, optics, k-mean clustering https://github.com/LukaszKrawczyk/density-clustering