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Low code machine learning library, specified for insurance tasks: prepare data, build model, implement into production.

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MindSetLib/Insolver

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Insolver

PyPI - Python Version PyPI Documentation Status GitHub Workflow Status Coverage Code style: black Downloads

Insolver is a low-code machine learning library, originally created for the insurance industry, but can be used in any other. You can find a more detailed overview here.

Installation:

Insolver can be installed via pip from PyPI. There are several installation options available:

Description Command
Regular installation pip install insolver
Installation with feature engineering requirements pip install insolver[feature_engineering]
Installation with feature monitoring requirements pip install insolver[feature_monitoring]
Installation with interpretation requirements pip install insolver[interpretation]
Installation with serving requirements pip install insolver[serving]
Installation with report requirements pip install insolver[report]
Installation with all requirements pip install insolver[all]

Insolver is already installed in the easy access cloud via the GitHub login. Try https://mset.space with a familiar notebook-style environment.

Examples:

Documentation:

Available here

Supported libraries:

GLM Boosting models Serving (REST-API) Model interpretation
- sklearn
- h2o
- XGBoost
- LightGBM
- CatBoost
- Flask
- FastAPI
- Django
- shap plots

Run tests:

python -m pytest

tests with coverage:

python -m pytest . --cov=insolver --cov-report html

Contributing to Insolver:

Please, feel free to open an issue or/and suggest PR, if you find any bugs or any enhancements.

Demo

Example of creating models using the Insolver

Example of a model production service

Example of an elyra pipeline built with the Insolver inside

Contacts

[email protected] +79263790123