Overview
Sequence transduction models are essential in the field of machine learning, particularly for tasks involving sequential data such as language translation and speech recognition. These models take an input sequence and transform it into an output sequence, leveraging architectures like Recurrent Neu...
Key Terms
Example: A sentence is a sequence of words.
Example: Neural networks can classify images.
Example: RNNs are used in language modeling.
Example: Attention is used in translation models to align words.
Example: Training a model involves adjusting its parameters.
Example: In translation, the output sequence is the translated sentence.