You need to train a natural language model to perform text classification on a dataset containing millions of product descriptions, with a vocabulary size of 100,000 unique words. To effectively preprocess the words so they can be fed into a recurrent neural network (RNN) for better performance, what preprocessing step should you take?

Exam-Like

Create a hot-encoding of words, and feed the encodings into your model.

10.9%

Identify word embeddings from a pre-trained model, and use the embeddings in your model.

78.1%

Sort the words by frequency of occurrence, and use the frequencies as the encodings in your model.

7.8%

Assign a numerical value to each word from 1 to 100,000 and feed the values as inputs in your model.

3.1%

Google Professional Machine Learning Engineer