dnouri/nolearn

Combines the ease of use of scikit-learn with the power of Theano/Lasagne

60
/ 100
Established

This project helps machine learning practitioners build and train deep neural networks for tasks like image recognition, object detection, and pattern classification. It takes structured data (like images or tabular data) and outputs trained models that can make predictions. It is primarily used by data scientists and researchers who work with deep learning and want to integrate it seamlessly into their existing scikit-learn workflows.

954 stars. No commits in the last 6 months. Available on PyPI.

Use this if you are a data scientist familiar with scikit-learn and want to train neural networks for tasks like facial keypoint detection or product classification.

Not ideal if you need a currently maintained deep learning library or prefer working with modern frameworks like PyTorch or TensorFlow directly.

deep-learning image-recognition data-science machine-learning predictive-modeling
Stale 6m No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 25 / 25
Community 25 / 25

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Stars

954

Forks

258

Language

Python

License

MIT

Last pushed

Jul 06, 2023

Commits (30d)

0

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