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CPSC 330 Lecture 7: imputation, scaling numeric features, `ColumnTransformer`
CPSC 330 Lecture 5: pipelines & hyperparameter optimization
CPSC 330 bonus segment: `SGDClassifier` and `SGDRegressor`
CPSC 330 Lecture 10: linear regression, scoring metrics for regression
CPSC 330 Lecture 17: time series data
CPSC 330 Lecture 18: survival analysis
#23: Scikit-learn 20: Preprocessing 20: Marking imputed values, MissingIndicator()
Missing Data: Imputation
MLOps Meetup #6: Mid-Scale Production Feature Engineering with Dr. Venkata Pingali
(Part 1) Using Column Transformer for making Machine Learning workflow easy | Machine Learning
Feature engineering in Machine Learning and Computer Vision by Ms Prerna Agarwal
Docker Series (Part 3 ) - Docker Storage
