PyCaret is a high-level, low-code Python library that makes it easy to compare, train, evaluate, tune, and deploy machine learning models with only a few lines of code . At its core, PyCaret is basically just a large wrapper over many data science libraries such as Scikit-learn, Yellowbrick, SHAP, Optuna, and Spacy.
Read moreHow does PyCaret work?
PyCaret is an open-source, low-code machine learning library in Python that aims to reduce the cycle time from hypothesis to insights.
Read moreIs sklearn used in production?
The variety of machine learning techniques in combination with the solid implementations that scikit-learn offers makes it a one-stop-shopping library for machine learning in Python . Moreover, its consistent API, well-tested code and permissive licensing allow us to use it in a production environment.
Read moreWhat is the use of PyCaret library?
PyCaret is a high-level, low-code Python library that makes it easy to compare, train, evaluate, tune, and deploy machine learning models with only a few lines of code . At its core, PyCaret is basically just a large wrapper over many data science libraries such as Scikit-learn, Yellowbrick, SHAP, Optuna, and Spacy.
Read moreIs PyCaret open-source?
PyCaret is completely free and open-source and licensed under the MIT license.
Read moreIs PyCaret an Automl?
PyCaret is an open-source, low-code machine learning library that helps Data Scientists to automate their machine learning workflows . It simplifies the model experimentation phase and there by allowing them to achieve desired results with minimal code.
Read moreDoes PyCaret use Sklearn?
The PyCaret regression module, which uses sklearn under the hood , lets you create and test regression models with a few lines of code. It includes a variety of algorithms, as well as the ability to plot and do hyperparameter tuning.
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