Sequence to Sequence Quiz (Easy)

What is the primary purpose of Sequence-to-Sequence (Seq2Seq) models in deep learning?

What is the key idea behind “attention mechanisms” in Seq2Seq models, and how do they improve performance

What is the primary architectural limitation of traditional Seq2Seq models based on recurrent neural networks (RNNs)?

In the context of machine translation, what role does the encoder in a Seq2Seq model play?

In RNNs, what is the “vanishing gradient” problem?

Which direction(s) can RNNs process sequences?

What is the primary motivation behind the development of Long Short-Term Memory (LSTM) networks?

What is the essential architectural difference between LSTMs and standard RNNs?