Data Science and Machine Learning (Theory and Projects) A to Z - RNN Architecture: OneToMany Model Exercise

The video tutorial discusses defining a loss function in a 1-to-many architecture, using image captioning as an example. It explains how a model takes one input and produces multiple outputs, and suggests implementing this using an encoder-decoder network. The tutorial also covers how to define a loss function for these outputs, considering them as words in a caption derived from training data.

In the context of the discussed architecture, what might the outputs represent?

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What considerations should be made when implementing a loss function for this architecture?

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