corgi VS DiffSharp

Compare corgi vs DiffSharp and see what are their differences.


A neural network, and tensor dynamic automatic differentiation implementation for Rust. (by patricksongzy)


DiffSharp: Differentiable Functional Programming (by DiffSharp)
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corgi DiffSharp
2 2
23 532
- 1.1%
0.0 0.0
almost 2 years ago about 2 months ago
Rust F#
MIT License BSD 2-clause "Simplified" 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.


Posts with mentions or reviews of corgi. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-04-06.


Posts with mentions or reviews of DiffSharp. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-04-22.

What are some alternatives?

When comparing corgi and DiffSharp you can also consider the following projects:

TensorFlow.NET - .NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C# and F#.

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

dfdx - Deep learning in Rust, with shape checked tensors and neural networks

autograd-rs - An autograd implementation in Rust

ocaml-torch - OCaml bindings for PyTorch

Java-Machine-Learning - Deep learning library for Java, with fully connected, convolutional, and recurrent layers. Also features many gradient descent optimization algorithms.

hyperlearn - 2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.