Questions

1. NLP transduction can encode and decode text representations. (True/False)
2. Natural Language Understanding (NLU) is a subset of Natural Language Processing (NLP). (True/False)
3. Language modeling algorithms generate probable sequences of words based on input sequences. (True/False)
4. A transformer is a customized LSTM with a CNN layer. (True/False)
5. A transformer does not contain LSTM or CNN layers. (True/False)
6. Attention examines all the tokens in a sequence, not just the last one. (True/False)
7. A transformer uses a positional vector, not positional encoding. (True/False)
8. A transformer contains a feedforward network. (True/False)
9. The masked multi-headed attention component of the decoder of a transformer prevents the algorithm parsing a given position from seeing the rest of a sequence that is being processed. (True/False)
10. Transformers can analyze long-distance dependencies better than LSTMs. (True/False)