Shaping and Transforming Features
Transform raw data into meaningful features using encoding, binning, and interaction terms. Enhance dataset representation by uncovering relationships within the data, paving the way for more insightful analysis and model building.
Lessons and practices
Identify Categorical Columns in Data
One-hot Encoding with Pandas
Refining One-Hot Encoding Parameters
One-hot Encode with Scikit-Learn
Label Encode the Titanic Data
Efficient Label Encoding with Loops
Fill in the Missing Bins
Binning Age Groups in Titanic Dataset
Fix Feature Binning Bug
Age Binning Challenge in Titanic Dataset
Insert Function Names for Transformations
Log Transformation in Titanic Dataset
Square Root Transformation in Action
From Square to Cube Roots
Creating a New Feature
Calculate Fare Per Person Feature
Identify Potential Couples
Creating a Family Size Category
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