{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/6"}],"enrichment":{"capability":"Extends scikit-learn with additional estimators and preprocessing tools designed to support SageMaker Autopilot, including dimension reduction, feature extraction, imputation, and encoding transformers.","skillfed_tags":["sagemaker-integration","dormant-maintenance","legacy-tool"],"use_cases":["Preprocess tabular data for SageMaker Autopilot by applying imputation and categorical encoding transformers.","Extract numeric features from datetime columns for time-aware machine learning models.","Handle extreme values and heavy-tailed distributions with specialized transformers.","Encode categorical features using supervised or similarity-based encoding methods.","Perform dimension reduction on sparse matrices without dense conversion.","Extract features from time-series sequence data using provided extractors."],"what_it_does":"SageMaker Scikit-Learn Extension is a collection of scikit-learn-compatible estimators and transformers built to fill gaps in scikit-learn's standard library and support AWS SageMaker's Autopilot automated machine learning service. It provides specialized tools for dimension reduction, feature extraction from datetime and time-series data, text vectorization, missing-value imputation with custom masking logic, and categorical encoding schemes. The package is designed as a repository for estimators that don't meet scikit-learn's strict inclusion criteria but are useful in production ML pipelines.\n\nThe project is dormant\u2014the last release was 2022-02-18, and it has not been updated since then. It is tested on Python 3.7 only. The package integrates with SageMaker's training containers and includes utilities for feature and target transformation, making it a legacy tool primarily suited for maintaining existing SageMaker workflows rather than new projects.","worth_installing":"No, unless you are maintaining an existing SageMaker Autopilot workflow. The package is dormant (last release 2022-02-18), has high install friction (requires conda for mlio version 0.7), and is tested only on Python 3.7. Compatibility with modern Python and scikit-learn versions is unverified. For new projects, use scikit-learn directly or actively-maintained alternatives."},"id":"sagemaker-scikit-learn-extension","links":{"html":"https://skillfed.io/packages/sagemaker-scikit-learn-extension","md":"https://skillfed.io/packages/sagemaker-scikit-learn-extension.md","pypi":"https://pypi.org/project/sagemaker-scikit-learn-extension/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2022-02-18","license_spdx":null,"license_treatment":"permissive","name":"sagemaker-scikit-learn-extension","python_support":"unspecified","summary":"Open source library extension of scikit-learn for Amazon SageMaker."},"popularity":{"monthly_downloads":302468,"position":7822,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.5.0"}