Machine Learning Toolkit

Haskell Machine Learning Toolkit includes various methods of supervised learning: linear regression, logistic regression, SVN, neural networks, etc. as well as some methods of unsupervised methods: K-Means and PCA.

Source code: github.


Amateur astronomical computations

Amateur astronomical computations: rise and set times and azimuths, coordinates, distances, angular sizes and other parameters of the Sun, the Moon, planets and stars.

Web UI: Astro UI.

Related tags: Astro.

Source code: github.


Implementation of a consensus algorithm Raft

The implementation supports basic features of the algorithm: leader election and log replication.

Related tags: raft.

Source code: github.


Discrete Optimization Library

Optimer library implements Branch and Bound Method along with various heuristics.

Related tags: Optimer.

Source code: github.


Basic statistics with some probability library

Includes common distributions (Bernoulli, Binomial, Poisson, Student’s and Normal), random number generators from some of the distributions, summary statistics for a sample, Z-Test, Student’s T-Test, special functions (Error, Gamma, Beta and Regularized Incomplete Beta).

Web UI: Statistics.

Related tags: statistics, FsStats.

Source code: github.


MIX Virtual Machine

Implementation of MIX Virtual Machine.

Related tags: mixvm.

Source code: github.