Preprocessing and Pipelines | Supervised Machine Learning with scikit-learn

Learn how to impute missing values, convert categorical data to numeric values, scale data, evaluate multiple supervised learning models simultaneously, and build pipelines to streamline your workflow!

Datasets

Links
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00:00 Course introduction
00:41 Chapter introduction
00:56 Preprocessing data
05:10 Handling missing data
08:26 Centering and Scaling
11:36 Evaluating multiple models
14:52 Congratulations