tensor-safe VS svm

Compare tensor-safe vs svm and see what are their differences.

tensor-safe

A Haskell framework to define valid deep learning models and export them to other frameworks like TensorFlow JS or Keras. (by leopiney)
AI Deep Learning haskell-library Dependent Types Functional programming Haskell Machine Learning
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svm

A support vector machine implemented in Haskell. (by andrewdougherty)
AI Svm
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tensor-safe svm
- -
101 33
- -
0.0 0.0
over 1 year ago over 13 years ago
Haskell Haskell
BSD 3-clause "New" or "Revised" License GNU General Public License v3.0 only
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.

tensor-safe

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

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

svm

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

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

What are some alternatives?

When comparing tensor-safe and svm you can also consider the following projects:

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.

nn - A tiny neural network 🧠

HSGEP - Haskell Gene Expression Programming Library

hnn - haskell neural network library

hasktorch - Tensors and neural networks in Haskell

heukarya - genetic programming in haskell

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

GA - Haskell module for working with genetic algorithms

csp - Constraint satisfaction problem (CSP) solvers for Haskell

opencv - Haskell binding to OpenCV-3.x

svm-simple - Simplified interface to bindings-svm

tensor-safe vs moo svm vs nn tensor-safe vs HSGEP svm vs hnn tensor-safe vs hasktorch svm vs heukarya tensor-safe vs cv-combinators svm vs HSGEP tensor-safe vs GA svm vs csp tensor-safe vs opencv svm vs svm-simple