Text Classification Quiz

Complete this assessment with 100% score to master this chapter.

01What is the goal of 'Sentiment Analysis'?

02Which evaluation metric is the harmonic mean of Precision and Recall?

03Why is 'Naive Bayes' often used as a baseline for text classification?

04What does an LSTM model provide that a simple 'Bag of Words' misses?

05In a text classification model, what is the purpose of the 'Embedding' layer?

06What is 'Cross-Entropy' loss used for in text classification?

07What is the 'Naive' assumption in a Naive Bayes classifier?

08In a multi-label classification task, what is the difference compared to multi-class?

09What does 'Zero-Shot' classification allow you to do?

10Why might you use 'Global Average Pooling' in a text model?