Algorithms for regression analysis (e.g. linear regression and logistic regression)
created at July 4, 2013, 1:36 p.m.
Regularized discriminant analysis in Julia.
created at Oct. 8, 2013, 3:48 a.m.
Julia wrapper for fitting Lasso/ElasticNet GLM models using glmnet
created at Nov. 19, 2013, 4:41 a.m.
A Julia framework for probabilistic graphical models.
created at March 20, 2014, 4:42 p.m.
A set of functions to support the development of machine learning algorithms
created at Feb. 10, 2013, 3:50 p.m.
MLPleaseHelp is a simple ML resource search engine.
created at Jan. 29, 2018, 3:15 a.m.
simple statistics for node & browser javascript
created at Feb. 8, 2012, 6:29 p.m.
Run XGBoost model and make predictions in Node.js
created at Sept. 9, 2017, 5:53 a.m.
Reinforcement learning using Markov Decision Processes. For JS, written in C++.
created at May 10, 2015, 4:52 p.m.
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
created at Jan. 23, 2015, 7:38 p.m.