Exploring and preprocessing data for ML.
6 practice questions under this official exam objective (PMLE), each with the answer key, an option-by-option explanation and instant feedback.
Questions under this objective
6 total · page 1 of 1Splitting Time-Signal Data for AutoML Tables
This PMLE question tests how AutoML Tables should partition tabular data when the time signal is spread across multiple columns. The correct answer is
Why a 99% Training AUC Signals Data Leakage, Not Overfitting
A 99% training AUC ROC achieved within a few experiments, without tuning or complex algorithms, indicates data leakage rather than overfitting. The co
Handling Missing Categorical Features in ML
Learn why treating missing values as a distinct category and creating an indicator variable is the optimal strategy for highly predictive categorical
BigQuery Cell Magic for pandas DataFrames in Notebooks
This PMLE question tests how to move BigQuery query results into pandas inside an AI Platform notebook, and the answer is A: run the query with the Bi
Feature Crosses for City-Specific ML Models
Learn how to build city-specific car sales prediction models using Google Cloud AI APIs by crossing binned geographic coordinates with categorical veh
Preventing Data Leakage in Time-Series Models via Temporal Splitting
This question addresses data leakage in time-series forecasting where random splitting inflates test accuracy. The correct approach is to use a tempor