fei-cocoapi VS tensor-safe

Compare fei-cocoapi vs tensor-safe 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)
Our great sponsors
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • WorkOS - The modern identity platform for B2B SaaS
  • SaaSHub - Software Alternatives and Reviews
fei-cocoapi tensor-safe
- -
0 101
- -
0.0 0.0
about 3 years ago over 1 year 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-cocoapi

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

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

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.

What are some alternatives?

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

fei-base - Yet another wrapper of mxnet in Haskell

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.

HSGEP - Haskell Gene Expression Programming Library

fei-examples

hasktorch - Tensors and neural networks in Haskell

finito - A constraint solver for finite domains, written in Haskell.

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

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

GA - Haskell module for working with genetic algorithms

opencv - Haskell binding to OpenCV-3.x