fastbayes VS statistics-linreg

Compare fastbayes vs statistics-linreg and see what are their differences.

fastbayes

A Haskell library for Bayesian modeling algorithms that are fast(er than general-purpose sampling). (by cscherrer)
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fastbayes statistics-linreg
- -
11 15
- -
0.0 0.0
almost 9 years ago over 9 years ago
Haskell Haskell
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

fastbayes

Posts with mentions or reviews of fastbayes. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning fastbayes yet.
Tracking mentions began in Dec 2020.

statistics-linreg

Posts with mentions or reviews of statistics-linreg. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning statistics-linreg yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing fastbayes and statistics-linreg you can also consider the following projects:

neural - Neural Nets in native Haskell

statistics - A fast, high quality library for computing with statistics in Haskell.

HLearn-algebra - Homomorphic machine learning

orgstat - Statistics visualizer for org-mode

rc - Reservoir Computing, an RNN flavor

inliterate - DiffusionKinetics open-source monorepo

order-statistics - L-estimators and order statistics

arrayfire - Haskell bindings to ArrayFire

genetics - A Genetic Algorithm library in Haskell

gauge - Lean Haskell Benchmarking

htvm - Haskell experiments involving TVM AI framework

haskell-ml - Various examples of machine learning, in Haskell.