Скачать или смотреть Overview of MLP weeks 1 to 4 content

The source outlines the comprehensive *Data Loading* and *Data Transformation* capabilities within the scikit-learn (sklearn) ecosystem, detailing various methods for acquiring and preparing data for machine learning. It explains three primary interfaces for accessing datasets: *Loaders* for bundled, small datasets, *Fetchers* for downloading larger datasets from the internet, and *Generators* for creating controlled synthetic datasets like those for regression or classification. The text also covers loading *external datasets* using tools like Pandas, SciPy, and specialized sklearn functions for different file formats and data types. Finally, it describes *transformers* for data cleaning, feature extraction, and reduction, along with tools like *Pipeline**, **FeatureUnion**, and **ColumnTransformer* for chaining and applying these transformations efficiently.