GA alternatives and similar packages

Based on the "AI" category.
Alternatively, view GA alternatives based on common mentions on social networks and blogs.

• grenade

  9.9 0.0 GA VS grenade

  Deep Learning in Haskell

• hasktorch

  9.9 5.4 GA VS hasktorch

  Tensors and neural networks in Haskell
  

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• opencv

  9.5 0.0 GA VS opencv

  Haskell binding to OpenCV-3.x
  

• hnn

  9.3 0.0 GA VS hnn

  haskell neural network library

• nn

  9.2 0.0 GA VS nn

  A tiny neural network 🧠

• tensor-safe

  8.8 0.0 GA VS tensor-safe

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

• moo

  8.6 0.0 GA VS moo

  Genetic algorithm library for Haskell. Binary and continuous (real-coded) GAs. Binary GAs: binary and Gray encoding; point mutation; one-point, two-point, and uniform crossover. Continuous GAs: Gaussian mutation; BLX-α, UNDX, and SBX crossover. Selection operators: roulette, tournament, and stochastic universal sampling (SUS); with optional niching, ranking, and scaling. Replacement strategies: generational with elitism and steady state. Constrained optimization: random constrained initialization, death penalty, constrained selection without a penalty function. Multi-objective optimization: NSGA-II and constrained NSGA-II.

• CV

  8.6 0.0 GA VS CV

  Haskell wrappers and utilities for OpenCV machine vision library

• keera-posture

  8.4 2.7 GA VS keera-posture

  Alleviate your back pain using Haskell and a webcam
  

• HOpenCV

  8.2 0.0 GA VS HOpenCV

  Haskell bindings for OpenCV

• svm

  7.8 0.0 GA VS svm

  A support vector machine implemented in Haskell.

• genprog

  7.6 0.0 GA VS genprog

  Genetic programming library

• hopfield

  7.5 0.0 GA VS hopfield

  hopfield
  

• svm-simple

  6.9 0.0 GA VS svm-simple

  Simplified interface to bindings-svm

• creatur

  6.9 0.0 GA VS creatur

  Framework for artificial life and other evolutionary algorithms.

• simple-genetic-algorithm

  6.9 0.0 GA VS simple-genetic-algorithm

  Simple parallel genetic algorithm implementation in pure Haskell

• cv-combinators

  6.7 0.0 GA VS cv-combinators

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

• csp

  6.5 0.0 GA VS csp

  Constraint satisfaction problem (CSP) solvers for Haskell

• neet

  6.4 0.0 GA VS neet

  Neuroevolution of Augmented Topologies (NEAT) -- in Haskell

• simple-neural-networks

  6.3 0.0 GA VS simple-neural-networks

  Simple parallel neural networks implementation in pure Haskell

• HaVSA

  6.1 0.0 GA VS HaVSA

  HaVSA (Have-Saa) is a Haskell implementation of the Version Space Algebra Machine Learning technique described by Tessa Lau.

• heukarya

  5.9 0.0 GA VS heukarya

  genetic programming in haskell

• HSGEP

  5.4 0.0 GA VS HSGEP

  Haskell Gene Expression Programming Library

• huff

  5.1 0.0 GA VS huff

  A fast-forward based planner for Haskell

• SimpleEA

  4.9 0.0 GA VS SimpleEA

  A simple evolutionary algorithm framework for Haskell

• smarties

  4.5 0.0 GA VS smarties

  haskell behavior tree library

• nondeterminism

  4.0 3.0 GA VS nondeterminism

  Nondeterministic computations in Haskell

• finito

  4.0 0.8 GA VS finito

  A constraint solver for finite domains, written in Haskell.

• fei-nn

  3.7 0.0 GA VS fei-nn

  High level APIs for leaveraging neural networks with MXNet in Haskell

• neural-network-base

  3.7 0.0 GA VS neural-network-base

  Neural network framework in Haskell

• hmep

  3.5 0.0 GA VS hmep

  Haskell Multi Expression Programming implemented with the focus on speed

• CarneadesDSL

  2.9 0.0 GA VS CarneadesDSL

  An implementation and DSL for the Carneades argumentation model.

• Etage

  2.2 0.0 GA VS Etage

  A general data-flow framework featuring nondeterminism, laziness and neurological pseudo-terminology.

• fei-base

  2.1 0.8 GA VS fei-base

  Yet another wrapper of mxnet in Haskell

• simple-genetic-algorithm-mr

  1.9 0.0 GA VS simple-genetic-algorithm-mr

  Fork of simple-genetic-algorithm using MonadRandom

• liblinear-enumerator

  1.9 0.0 L1 GA VS liblinear-enumerator

  Haskell bindings to liblinear

• mxnet-nn

  1.8 GA VS mxnet-nn

  Train a neural network with MXNet in Haskell.

• fei-dataiter

  1.6 0.0 GA VS fei-dataiter

  Data Loading API of mxnet in Haskell

• fei-examples

  1.6 0.0 GA VS fei-examples

  fei examples

• fei-cocoapi

  1.4 0.0 GA VS fei-cocoapi

  Cocodataset with cocoapi

• attoparsec-arff

  0.8 0.0 GA VS attoparsec-arff

  An attoparsec-based parser for ARFF files in Haskell

• sandlib

  - - GA VS sandlib

  SAND data serialization and manipulation library

• mxnet-dataiter

  - GA VS mxnet-dataiter

  mxnet dataiters

* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.

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Popular Comparisons

• GA
  vs
  hnn
• GA
  vs
  mxnet-nn
• grenade
  vs
  simple-neural-networks
• hasktorch
  vs
  grenade
• mxnet-nn
  vs
  opencv

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