Build a regularized regression pipeline

You are given a clean historical marketing dataset. Predict the number of signups from spend, clicks, cpc, region, and a time index derived from date. Implement the solution in scikit-learn with these components: Build a ColumnTransformer where numeric columns (spend, clicks, cpc, time_index) are scaled by StandardScaler and region is encoded by OneHotEncoder(handle_unknown='ignore'). Diagnose whether the target should be modeled on its original scale or after applying…