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Menu iconMenu iconNatural Language Processing con Python Edición Actualizada
Natural Language Processing con Python Edición Actualizada

Quiz Part II: Advanced Text Processing and Modeling

Chapter 4: Language Modeling

  1. What is an N-gram?
    • A) A type of neural network
    • B) A sequence of N words used for language modeling
    • C) A text classification method
    • D) A type of sentiment analysis
  2. Which of the following problems does a Hidden Markov Model (HMM) address?
    • A) Evaluation Problem
    • B) Decoding Problem
    • C) Learning Problem
    • D) All of the above
  3. What is the primary advantage of using Long Short-Term Memory (LSTM) networks over standard RNNs?
    • A) They are easier to train
    • B) They can capture long-range dependencies
    • C) They require less data
    • D) They are more interpretable

Chapter 4: Language Modeling

  1. What is an N-gram?
    • A) A type of neural network
    • B) A sequence of N words used for language modeling
    • C) A text classification method
    • D) A type of sentiment analysis
  2. Which of the following problems does a Hidden Markov Model (HMM) address?
    • A) Evaluation Problem
    • B) Decoding Problem
    • C) Learning Problem
    • D) All of the above
  3. What is the primary advantage of using Long Short-Term Memory (LSTM) networks over standard RNNs?
    • A) They are easier to train
    • B) They can capture long-range dependencies
    • C) They require less data
    • D) They are more interpretable

Chapter 4: Language Modeling

  1. What is an N-gram?
    • A) A type of neural network
    • B) A sequence of N words used for language modeling
    • C) A text classification method
    • D) A type of sentiment analysis
  2. Which of the following problems does a Hidden Markov Model (HMM) address?
    • A) Evaluation Problem
    • B) Decoding Problem
    • C) Learning Problem
    • D) All of the above
  3. What is the primary advantage of using Long Short-Term Memory (LSTM) networks over standard RNNs?
    • A) They are easier to train
    • B) They can capture long-range dependencies
    • C) They require less data
    • D) They are more interpretable

Chapter 4: Language Modeling

  1. What is an N-gram?
    • A) A type of neural network
    • B) A sequence of N words used for language modeling
    • C) A text classification method
    • D) A type of sentiment analysis
  2. Which of the following problems does a Hidden Markov Model (HMM) address?
    • A) Evaluation Problem
    • B) Decoding Problem
    • C) Learning Problem
    • D) All of the above
  3. What is the primary advantage of using Long Short-Term Memory (LSTM) networks over standard RNNs?
    • A) They are easier to train
    • B) They can capture long-range dependencies
    • C) They require less data
    • D) They are more interpretable