skorch
Scikit-learn compatible neural network library wrapping PyTorch.
Pricing
Free tier
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is skorch?
Skorch is a scikit-learn compatible neural network library that wraps the popular deep learning framework PyTorch. It provides a high-level interface for training and deploying neural networks while maintaining compatibility with other scikit-learn tools.
Key differentiator
“Skorch uniquely bridges the gap between scikit-learn and PyTorch, offering a familiar API to machine learning practitioners while enabling them to leverage the power of deep neural networks.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, which may be unfamiliar to developers from other language backgrounds.
The niche nature of Skorch as a scikit-learn wrapper for PyTorch means fewer resources and slower response times for issues.
The high-level interface adds an extra layer, which can introduce performance penalties compared to direct PyTorch usage.
As a less mainstream tool within the deep learning community, Skorch's documentation may lag behind updates or new features in PyTorch itself.
Fit analysis
Who is it for?
✓ Best for
Developers who need to integrate PyTorch-based models into scikit-learn workflows
Data scientists familiar with scikit-learn but looking to leverage deep learning capabilities
✕ Not a fit for
Projects requiring real-time inference as skorch is primarily for training and model deployment
Teams needing a fully managed service or cloud-based solution, as it's self-hosted
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Alternatives
Works well with
Next step
Get Started with skorch
Step-by-step setup guide with code examples and common gotchas.