This quiz is designed to test your understanding of intermediate-level concepts in Natural Language Processing (NLP). It covers topics such as tokenization, embeddings, language models, text preprocessing, and common NLP techniques. You’ll also encounter questions on libraries like NLTK, spaCy, and Hugging Face, as well as challenges in sentiment analysis, named entity recognition (NER), and transformer-based models.

NLP Medium Quiz 6

NLP's main objective is to allow machines to process, understand, and interact with human language, whether it's in text or speech form. This involves tasks like language translation, sentiment analysis, and text generation.

1 / 10

Which of the following is a pre-trained language model used in NLP?

2 / 10

In Word2Vec, what does the 'skip-gram' model do?

3 / 10

Which of the following is a common challenge in NLP?

4 / 10

Which algorithm is typically used for text classification tasks in NLP?

5 / 10

Which of the following is an example of a named entity in NLP?

 

6 / 10

Which of the following is an example of a bag-of-words (BoW) model?

7 / 10

What is tokenization in NLP?

8 / 10

Which of the following techniques is used for part-of-speech tagging in NLP?

9 / 10

Which of the following is a common application of NLP?

10 / 10

What is the main goal of Natural Language Processing (NLP)?

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