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Data Preparation & Cleaning for Machine Learning
Introduction
Introduction (1:01)
Note to students from Andrew Jones
ML Prep Checklist (7:17)
Working with Missing Values
Theory Missing Values (8:47)
Missing Values with Pandas (12:42)
Missing Values with SimpleImputer (11:05)
Missing Values with KNNImputer (11:49)
Theory Categorical Variables (8:18)
Categorical Variables One-Hot-Encoding (10:50)
Outliers & Feature Scaling
Theory Outliers (8:55)
Outliers hands-on (13:34)
Theory Feature Scaling (9:19)
Feature Scaling hands-on (8:18)
Feature Selection
Theory Feature Selection (12:04)
Feature Selection Data
Practical Correlation Matrix (4:26)
Practical Univariate Testing (17:53)
Practical RFECV (13:48)
ML Model Validation
Theory Model Validation (8:53)
Practical Model Validation (18:06)
Categorical Variables One-Hot-Encoding
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