Question 12
Domain 2: Explore data and run experimentsYou are junior data scientist of your company. You are building a machine learning model for translating English language textual content into French language textual content. You need to build and train the machine learning model to learn the sequence of the textual content. Which type of neural network should you use?
Correct answer: C
Explanation
Recurrent Neural Networks (RNNs) are used for sequence learning because they process data in order and retain information from earlier steps. For translation, the model must learn the relationship between words across a sentence, and RNNs are designed to handle “sequence of the textual content.”
Why each option is right or wrong
A. Multilayer Perceptions (MLPs)
B. Convolutional Neural Networks (CNNs)
C. Recurrent Neural Networks (RNNs)
Sequence-to-sequence translation requires a model that processes tokens in order and carries forward state from earlier words to later ones; that is the defining behavior of recurrent neural networks under the standard RNN formulation, where the hidden state at time t depends on x_t and the previous hidden state h_{t-1}. In practice, this is why RNN-based encoder–decoder models are used for sentence translation tasks, unlike feedforward networks that have no temporal dependency handling.
D. Generative Adversarial Networks (GANs)