Scikit-learn is the most widely used general purpose machine learning library in Python. It has a very nice API and many tools are built around it, but its support for neural networks is very limited.

PyTorch is a deep learning platform that makes working with neural networks a blast. However, users often find that they need to write boilerplate and wrapper code to integrate PyTorch into their existing workflows.

A possible solution to those problems is skorch. This open source Python library allows you to easily wrap your PyTorch modules to give them a high level sklearn API. This allows you to:

• tap into the power and flexibility of PyTorch
• get rid of most of the boring boilerplate code
• combine PyTorch nets with the usual sklearn goodies like Pipelines, GridSearchCV, etc.

Ideally, you already have some basic knowledge of sklearn and PyTorch, or are an advanced user of one of the two libraries who is curious about improving your workflow.

Benjamin Bossan

Affiliation: NewYorker

Data Scientist at NewYorker

visit the speaker at: Github