| grenade | nn | |
|---|---|---|
| 5 | - | |
| 1,445 | 125 | |
| - | - | |
| 5.6 | 0.0 | |
| 9 months ago | over 6 years ago | |
| Haskell | Haskell | |
| BSD 2-clause "Simplified" License | MIT License |
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.
grenade
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Haskell deep learning tutorials [Blog]
Grenade is fun, but it does not support CUDA, so it will limit you. I would say that this was a great experiment that has influenced the Hasktorch library in different ways (let me know if I am wrong).
- Dhall: A Gateway Drug to Haskell
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Haskell for Artificial Intelligence?
FWIW there's an interesting library called grenade which offers nice types for constructing neural nets. I haven't used it, and this is not my areas of expertise, but it looks cool!
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Rank 3 Stencils for "Efficient Parallel Stencil Convolution in Haskell" (Repa)
When I wrote grenade I used the im2col trick to turn convolutions into a single matrix multiplication, which could then be done in hmatrix.
- What are some ways I could tickle my (beginner) haskell-brain with something *useful*?
nn
We haven't tracked posts mentioning nn yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
hasktorch - Tensors and neural networks in Haskell
fei-examples
liblinear-enumerator - Haskell bindings to liblinear
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.
simple-neural-networks - Simple parallel neural networks implementation in pure Haskell
svm - A support vector machine implemented in Haskell.
CV - Haskell wrappers and utilities for OpenCV machine vision library
fei-base - Yet another wrapper of mxnet in Haskell
csp - Constraint satisfaction problem (CSP) solvers for Haskell
finito - A constraint solver for finite domains, written in Haskell.
hnn - haskell neural network library
huff - A fast-forward based planner for Haskell