If you transition to a legitimate dataset, here is the standard workflow for preparing features:
: Handle missing values by using imputation (mean/median) or dropping incomplete rows. 900k_USA_dump.txt
: Provides extensive, anonymized USA demographic data for feature engineering. How to Prepare Features for a Standard Dataset If you transition to a legitimate dataset, here
: Offers thousands of structured datasets (CSV, JSON) for tasks like credit scoring, housing prices, or demographic analysis. JSON) for tasks like credit scoring
: Create new variables, such as calculating "Years of Credit History" from "Account Open Date."