Foundations of Feature Engineering
Master the basics of feature engineering by learning to clean, handle missing data, scale, and normalize datasets. Prepare raw data for transformation and analysis, setting a solid foundation for advanced data engineering tasks.
Lessons and practices
Loading The Titanic Dataset
Exploring Dataset Structure
Peek at Your Data Preview
Customize Data Preview Settings
Understanding Numbers Through Statistics
Detecting Missing Data Like a Pro
Missing Ages Need Fixing
Switching to Mean Imputation for Missing Ages
Mode Imputation for Missing Ports
Missing Data Handling for Passenger Decks
Calculating Quartiles for Outlier Detection
Adjusting Outlier Detection Sensitivity
Outliers in Need of Detection
Capping Outliers Effectively
Scale Your First Dataset
Moving to Standard Scaling
Data Scaling Gone Wrong
Reverting Scaled Data in Practice
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