Build and evaluate machine learning models in Python.
What it does
Guides the development of scikit-learn models and pipelines for preparing data, training models, and evaluating predictions.
When to use it
Use when building predictive models, clustering data, preprocessing features, evaluating models, tuning hyperparameters, or creating machine learning pipelines.
How to use it
It changes how the agent develops machine learning code by guiding algorithm selection, preprocessing, evaluation, and pipeline construction.
What you provide
- An existing project
Good to know
- works out of sight
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What you need · 2
The examples run in Python; no Python version is specified.
The guide centers on the scikit-learn library and uses its model selection, preprocessing, model, and evaluation APIs.
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