TensorFlow.jl
A Julia wrapper for TensorFlow (by malmaud)
FiniteDiff.jl
Fast non-allocating calculations of gradients, Jacobians, and Hessians with sparsity support (by JuliaDiff)
TensorFlow.jl | FiniteDiff.jl | |
---|---|---|
1 | 1 | |
879 | 238 | |
- | 2.5% | |
0.0 | 6.5 | |
almost 3 years ago | 17 days ago | |
Julia | Julia | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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.
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.
TensorFlow.jl
Posts with mentions or reviews of TensorFlow.jl.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-06-16.
-
Flux vs. TensorFlow
My understanding is that Tensorflow.jl does not wrap the Python library, but the underlying C implementation. So it was an alternative to the Python version, not just a wrapper of it, and this gave it some advantages: https://github.com/malmaud/TensorFlow.jl/blob/master/docs/src/why_julia.md
FiniteDiff.jl
Posts with mentions or reviews of FiniteDiff.jl.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-08-25.
-
Question About Numerical Derivatives/Gradients: Why has no one yet implemented a gradient function in Julia that is similar to the gradient function in MATLAB and NumPy?
There is a finite difference gradient in https://github.com/JuliaDiff/FiniteDiff.jl
What are some alternatives?
When comparing TensorFlow.jl and FiniteDiff.jl you can also consider the following projects:
Zygote.jl - 21st century AD
ForwardDiff.jl - Forward Mode Automatic Differentiation for Julia
julia - The Julia Programming Language
CUDA.jl - CUDA programming in Julia.
FastAI.jl - Repository of best practices for deep learning in Julia, inspired by fastai
NDTensors.jl - A Julia package for n-dimensional sparse tensors.
Vulkan.jl - Using Vulkan from Julia
Oceananigans.jl - 🌊 Julia software for fast, friendly, flexible, ocean-flavored fluid dynamics on CPUs and GPUs
Metal.jl - Metal programming in Julia
ReLambertW.jl - Fast real valued Lambert W and Wright omega functions for Julia.
MLJ.jl - A Julia machine learning framework
Makie.jl - Interactive data visualizations and plotting in Julia
TensorFlow.jl vs Zygote.jl
FiniteDiff.jl vs ForwardDiff.jl
TensorFlow.jl vs julia
FiniteDiff.jl vs CUDA.jl
TensorFlow.jl vs FastAI.jl
FiniteDiff.jl vs NDTensors.jl
TensorFlow.jl vs Vulkan.jl
FiniteDiff.jl vs Oceananigans.jl
TensorFlow.jl vs Metal.jl
FiniteDiff.jl vs ReLambertW.jl
TensorFlow.jl vs MLJ.jl
FiniteDiff.jl vs Makie.jl