What is Natural Language Processing (NLP)?

• The field of computer science that focuses on understanding formal languages used in programming.

• The field of artificial intelligence that focuses on the understanding and generation of human language by computers.

• The field of mathematics that focuses on creating and solving complex algorithms.

• The field of engineering that focuses on designing and building robots.

What is a language model?

• A program used to translate languages.

• A subset of models that can generate, understand, or manipulate text or speech in natural language.

• A program that can recognize images.

• A program used for creating mathematical formulas.

Which of the following is an example of a statistical language model?

• BERT

• GPT

• N-grams

• Llama 2

What is a key limitation of n-gram models?

• They are computationally expensive to train.

• They are not suitable for text classification.

• They exhibit limitations in capturing long-range dependencies.

• They cannot be used for text generation.

What is the main characteristic of a trigram model?

• It considers the preceding single word.

• It considers the preceding two words.

• It considers the entire sentence.

• It considers the entire paragraph.

What is a key feature of contextual language models?

• They are based on statistical analysis of word probabilities.

• They combine NLP techniques with a structured knowledge base.

• They can understand the meaning of words based on their context.

• They are the simplest type of neural network.

Which of the following is an example of a contextual language model?

• BERT

• GPT

• N-grams

• ELMo

How are neural network-based models inspired?

• By the human brain.

• By the structure of a tree.

• By the flow of water in a river.

• By the movement of planets.

What is the simplest type of neural network?

• Recurrent Neural Network (RNN)

• Gated Recurrent Unit (GRU)

• Long Short-Term Memory (LSTM)

• Feedforward Neural Network

What is the main advantage of Recurrent Neural Networks (RNNs) over traditional feedforward networks?

• They are simpler to design.

• They can recognize images.

• They have the ability to retain information from previous steps in a sequence.

• They are faster to train.