fei-examples VS smarties

Compare fei-examples vs smarties and see what are their differences.

smarties

haskell behavior tree library (by minimapletinytools)
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fei-examples smarties
- -
1 11
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0.0 0.0
about 3 years ago about 4 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.

fei-examples

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

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

smarties

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

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

What are some alternatives?

When comparing fei-examples and smarties you can also consider the following projects:

nn - A tiny neural network 🧠

genprog - Genetic programming library

fei-base - Yet another wrapper of mxnet in Haskell

GA - Haskell module for working with genetic algorithms

fei-nn - High level APIs for leaveraging neural networks with MXNet in Haskell

HOpenCV - Haskell bindings for OpenCV

fei-cocoapi

creatur - Framework for artificial life and other evolutionary algorithms.

fei-dataiter - Data Loading API of mxnet in Haskell

cv-combinators - Functional Combinators for Computer Vision, currently using OpenCV as a backend

HSGEP - Haskell Gene Expression Programming Library

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