Brokttv/optimizers-from-scratch

training models with different optimizers using NumPy only. Featuring SGD, Adam, Adagrad, NAG, RMSProp, and Momentum. This repo also includes a benchmark against Pytorch developed optims.

22
/ 100
Experimental

No commits in the last 6 months.

Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 5 / 25
Maturity 9 / 25
Community 6 / 25

How are scores calculated?

Stars

13

Forks

1

Language

Jupyter Notebook

License

MIT

Category

gradient-descent-optimizers

Last pushed

Sep 09, 2025

Commits (30d)

0

GitHub
Gradient Descent Optimizers · 67 frameworks

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Brokttv/optimizers-from-scratch"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.

Higher-rated alternatives

metaopt/torchopt

TorchOpt is an efficient library for differentiable optimization built upon PyTorch.

61

opthub-org/pytorch-bsf

PyTorch implementation of Bezier simplex fitting

58

SimplexLab/TorchJD

Library for Jacobian descent with PyTorch. It enables the optimization of neural networks with...

58

pytorch/xla

Enabling PyTorch on XLA Devices (e.g. Google TPU)

57

clovaai/AdamP

AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights (ICLR 2021)

55

Explore ML Frameworks

All categories Trending ML Framework directory Insights