GDPR primarily focuses on:

The most common similarity measure in text mining is:

Which best defines a data pipeline?

In reinforcement learning, an agent learns through trial and error by receiving rewards or penalties. 

Training, validation, and test splits are used to prevent overfitting in AI models.

Domain-specific vocabulary always guarantees higher accuracy in sentiment analysis.

Heteroscedasticity violates a core regression assumption about equal error variance. 

Topic modeling is an unsupervised method for discovering themes.

A/B testing compares multiple versions of a webpage to measure performance differences. 

Logistic regression is suitable for predicting continuous outcomes.