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SKORCH

scikit-learn compatible neural network library for PyTorch

BSD-3-Clause

ABOUT

PyTorch provides powerful deep learning primitives but lacks the high-level training abstractions that scikit-learn users expect, such as fit/predict interfaces, grid search, and cross-validation. This creates a steep learning curve for data scientists who want to adopt neural networks without rewriting their entire ML pipeline. Skorch bridges this gap by wrapping PyTorch modules in a scikit-learn compatible estimator interface, enabling seamless integration with existing scikit-learn workflows, pipelines, and model selection.

INSTALL
pip install skorch

INTEGRATION GUIDE

1. Train PyTorch neural networks using familiar scikit-learn fit and predict methods 2. Perform hyperparameter tuning with scikit-learn GridSearchCV on PyTorch models 3. Build ensemble models combining PyTorch neural networks with traditional ML estimators 4. Deploy PyTorch models in production pipelines designed for scikit-learn interfaces 5. Migrate existing scikit-learn workflows to deep learning without pipeline rewrites

TAGS

pytorchscikit-learnneural-networksmachine-learningpythonopen-source
Skorch — AI Tool | Agentic AI For Good