simple-neural-networks VS GA

Compare simple-neural-networks vs GA and see what are their differences.

simple-neural-networks

Simple parallel neural networks implementation in pure Haskell (by afiskon)

GA

Haskell module for working with genetic algorithms (by boegel)
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simple-neural-networks GA
- -
12 19
- -
0.0 0.0
over 6 years ago over 12 years ago
Haskell Haskell
BSD 3-clause "New" or "Revised" License BSD 3-clause "New" or "Revised" 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.

simple-neural-networks

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

We haven't tracked posts mentioning simple-neural-networks yet.
Tracking mentions began in Dec 2020.

GA

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

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

What are some alternatives?

When comparing simple-neural-networks and GA you can also consider the following projects:

grenade - Deep Learning in Haskell

hopfield - hopfield

hnn - haskell neural network library

genprog - Genetic programming library

simple-genetic-algorithm - Simple parallel genetic algorithm implementation in pure Haskell

simple-genetic-algorithm-mr - Fork of simple-genetic-algorithm using MonadRandom

HOpenCV - Haskell bindings for OpenCV

smarties - haskell behavior tree library

keera-posture - Alleviate your back pain using Haskell and a webcam

tensor-safe - A Haskell framework to define valid deep learning models and export them to other frameworks like TensorFlow JS or Keras.