yeliudev/nncore
📦 A lightweight machine learning toolkit for researchers, providing common model design & learning functionalities.
This toolkit helps machine learning and deep learning researchers streamline their model development and experimentation. It takes care of repetitive engineering tasks like data loading, distributed training setup, and checkpoint management, allowing you to focus on the scientific aspects of your research. This project is for researchers who build and test machine learning models.
No commits in the last 6 months. Available on PyPI.
Use this if you are a machine learning researcher who wants to accelerate your model development by automating common engineering tasks in your training and testing workflows.
Not ideal if you are looking for a high-level, off-the-shelf solution for applying existing machine learning models without extensive custom research and development.
Stars
28
Forks
2
Language
Python
License
MIT
Category
Last pushed
Jul 02, 2025
Commits (30d)
0
Dependencies
10
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/yeliudev/nncore"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
pytorch/pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
keras-team/keras
Deep Learning for humans
Lightning-AI/torchmetrics
Machine learning metrics for distributed, scalable PyTorch applications.
Lightning-AI/pytorch-lightning
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
lanpa/tensorboardX
tensorboard for pytorch (and chainer, mxnet, numpy, ...)