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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is self-supervised learning?
💡 Hint: Think about a way to learn from data without needing labels.
Question 2
Easy
What are masked prediction models?
💡 Hint: Consider how BERT processes sentences.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the main goal of self-supervised learning?
- To learn from labeled data
- To learn from structured data
- To learn from unlabeled data
💡 Hint: Think about the limitations of requiring labeled data.
Question 2
True or False: In contrastive learning, the aim is to maximize the similarity between dissimilar pairs.
- True
- False
💡 Hint: Consider the definitions of similarity and dissimilarity.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Explain how contrastive learning could be used to differentiate between two types of fruit images. What features would the model focus on?
💡 Hint: Think about what makes an apple different from an orange.
Question 2
Design a small dataset for training a masked prediction model in text. What kinds of sentences would be suitable, and what techniques would you employ for masking?
💡 Hint: Consider generating sentences with meaningful context for the model to predict.
Challenge and get performance evaluation