neural-network-base VS CarneadesDSL

Compare neural-network-base vs CarneadesDSL and see what are their differences.

neural-network-base

Neural network framework in Haskell (by pierric)
AI Neural
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CarneadesDSL

An implementation and DSL for the Carneades argumentation model. (by nebasuke)
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neural-network-base CarneadesDSL
- -
5 2
- -
0.0 0.0
over 6 years ago over 9 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.
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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.

neural-network-base

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

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

CarneadesDSL

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

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

What are some alternatives?

When comparing neural-network-base and CarneadesDSL you can also consider the following projects:

hnn - haskell neural network library

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

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.

creatur - Framework for artificial life and other evolutionary algorithms.

GA - Haskell module for working with genetic algorithms

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

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

attoparsec-arff - An attoparsec-based parser for ARFF files in Haskell

genprog - Genetic programming library

HSGEP - Haskell Gene Expression Programming Library

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

neural-network-base vs hnn CarneadesDSL vs hnn neural-network-base vs keera-posture CarneadesDSL vs moo neural-network-base vs creatur CarneadesDSL vs GA neural-network-base vs Etage CarneadesDSL vs tensor-safe neural-network-base vs attoparsec-arff CarneadesDSL vs genprog neural-network-base vs HSGEP CarneadesDSL vs cv-combinators