This is the Windows app named micrograd whose latest release can be downloaded as microgradsourcecode.zip. It can be run online in the free hosting provider OnWorks for workstations.
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SCREENSHOTS:
micrograd
DESCRIPTION:
micrograd is a tiny, educational automatic differentiation engine focused on scalar values, built to show how backpropagation works end to end with minimal code. It constructs a dynamic computation graph as you perform math operations and then computes gradients by walking that graph backward, making it an approachable “from scratch” autograd reference. On top of the core autograd “Value” concept, the project includes a small neural network library that lets you define and train simple models with a PyTorch-like feel, including multilayer perceptrons. The repository is intentionally compact and readable, prioritizing clarity over performance so learners can follow every step of gradient flow and parameter updates. It is commonly used as a learning bridge between basic calculus intuition and full-scale deep learning frameworks, helping developers understand why autodiff libraries behave the way they do.
Features
- Scalar-valued automatic differentiation engine
- Dynamic computation graph construction
- Backpropagation with gradient accumulation
- Minimal neural network utilities on top
- PyTorch-like training patterns for small models
- Reference-style tests and demos for learning
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/micrograd.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.