ploomber/sklearn-evaluation
A Python library for evaluating machine learning models with plots, reports, and experiment tracking.
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sklearn-evaluation is a Python library that simplifies ML model evaluation by generating plots, tables, and HTML reports. It provides experiment tracking capabilities and integrates with Jupyter notebooks for interactive analysis. The library supports multiple ML frameworks including scikit-learn, PyTorch, and TensorFlow, making it a versatile tool for data scientists evaluating model performance.
Frequently asked
- What is ploomber/sklearn-evaluation?
- A Python library for evaluating machine learning models with plots, reports, and experiment tracking.
- Is sklearn-evaluation open source?
- Yes — ploomber/sklearn-evaluation is open source, released under the Apache-2.0 license.
- What language is sklearn-evaluation written in?
- ploomber/sklearn-evaluation is primarily written in Python.
- How popular is sklearn-evaluation?
- ploomber/sklearn-evaluation has 467 stars on GitHub.
- Where can I find sklearn-evaluation?
- ploomber/sklearn-evaluation is on GitHub at https://github.com/ploomber/sklearn-evaluation.