In the context of preparing a dataset for a machine learning project aimed at predicting customer churn for a telecommunications company, why is data cleaning considered a crucial step? Choose the two most accurate statements from the options below. (Choose two)

Real Exam

It simplifies the dataset by removing unnecessary columns, thereby reducing computational overhead.

2.6%

It ensures the accuracy and reliability of the dataset by correcting errors and handling missing values.

47.4%

It eliminates the need for feature engineering by automatically selecting the most relevant features.

0.0%

It guarantees the dataset's compliance with global data protection regulations without further checks.

5.3%

It improves the model's performance by normalizing data scales and removing outliers that could skew predictions.

44.7%

Google Professional Machine Learning Engineer