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Awesome GitHub RepositoriesImperative Data Transformations
Manual step-by-step mutations of datasets to achieve specific target formats.
Distinct from Step Data Mappers: Distinct from DOM mutations or execution engines; focuses on manual data reshaping for textbook output.
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Awesome Imperative Data Transformations GitHub Repositories
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- jwarmenhoven/islr-python
JWarmenhoven/ISLR-python
4,398Auf GitHub ansehenThis project is a machine learning education resource consisting of Python implementations of statistical learning models and data analysis examples from a core textbook. It serves as a statistical modeling library that provides the code necessary to implement linear regression, classification, and unsupervised learning techniques for academic data analysis. The repository is structured as a reference-driven implementation, with a directory layout that mirrors the chapter and section hierarchy of the associated academic publication. It includes a set of scripts and notebooks designed to gener
Provides manual step-by-step data mutations to match expected textbook output formats.
Jupyter Notebook
