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

The video tutorial discusses image captioning, focusing on the use of one hot vectors to represent labels. It explains how the length of these vectors corresponds to the vocabulary of the target language. The tutorial also covers the concept of probability vectors and how cross entropy loss is computed using these vectors. Finally, it highlights the similarities in defining loss functions across different architectures.

What does the true vector represent in the context of the ith timestep?

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Describe how losses for all time steps can be aggregated in the loss function.

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