Web Reference: 7.3. Preprocessing data # The sklearn.preprocessing package provides several common utility functions and transformer classes to change raw feature vectors into a representation that is more suitable for the downstream estimators. 3 days ago · Scikit-learn Preprocessing: Turning Raw Data Into Something a Model Can Learn From Raw data is almost never model-ready. Categories are stored as words, numbers live on wildly different scales, and models that expect clean numerical input will either crash or quietly produce terrible results if you hand them unprocessed data. Learn how to preprocess data for machine learning using scikit-learn. This lab covers feature scaling with StandardScaler and categorical encoding with LabelEncoder.
YouTube Excerpt: The video discusses what, why and when is standardization or mean removal or variance scaling needed. Then shows how to ...

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