machine.academy VS SoftGround

Compare machine.academy vs SoftGround and see what are their differences.

SoftGround

High performance runtime collider deformation in Unity (by aleksandrpp)
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machine.academy SoftGround
1 1
11 1
- -
7.6 3.0
5 months ago 12 months ago
C# C#
GNU General Public License v3.0 only MIT 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.

machine.academy

Posts with mentions or reviews of machine.academy. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-01-04.
  • Neural Network from Scratch
    6 projects | news.ycombinator.com | 4 Jan 2022
    Nice! I made a gpu accelerated backpropagation lib a while ago to learn about NNs, if you are interested check it out here: https://github.com/zbendefy/machine.academy

SoftGround

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

What are some alternatives?

When comparing machine.academy and SoftGround you can also consider the following projects:

ML-From-Scratch - Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

InteractiveSmoke - Counter-Strike 2 responsive smoke w/ Unity Compute Shader

micrograd - A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API

Amplifier.NET - Amplifier allows .NET developers to easily run complex applications with intensive mathematical computation on Intel CPU/GPU, NVIDIA, AMD without writing any additional C kernel code. Write your function in .NET and Amplifier will take care of running it on your favorite hardware.

GazeTracker - Artificial intelligence tracker for OpenTrack

ILGPU - ILGPU JIT Compiler for high-performance .Net GPU programs

Numerical-Realization - An English-based natural language generator for numerical inputs.

Cekirdekler - Multi-device OpenCL kernel load balancer and pipeliner API for C#. Uses shared-distributed memory model to keep GPUs updated fast while using same kernel on all devices(for simplicity).

deepnet - Educational deep learning library in plain Numpy.

ILSpy - .NET Decompiler with support for PDB generation, ReadyToRun, Metadata (&more) - cross-platform!

Numerical-Realization - An English-based natural language generator for numerical inputs.

ComputeSharp - A .NET library to run C# code in parallel on the GPU through DX12, D2D1, and dynamically generated HLSL compute and pixel shaders, with the goal of making GPU computing easy to use for all .NET developers! 🚀