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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the primary purpose of word embeddings?
💡 Hint: Consider how computers handle language.
Question 2
Easy
How does the Skip-gram model function in word2vec?
💡 Hint: Think about what the model uses as input.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What does word2vec primarily do?
💡 Hint: Think about word representation.
Question 2
True or False: GloVe uses local word contexts to create word vectors.
💡 Hint: Consider the difference between local and global statistics.
Solve 2 more questions and get performance evaluation
Push your limits with challenges.
Question 1
A company wants to implement sentiment analysis using an NLP model. Discuss whether they should use static or contextual embeddings and justify your choice.
💡 Hint: Think about how emotions can change in different contexts.
Question 2
Imagine you need to build a chatbot that understands varied phrasing related to banking services. Discuss which embedding technique would be most suitable and why.
💡 Hint: Consider how phrases can be interpreted in multiple ways.
Challenge and get performance evaluation