Data Science and Machine Learning (Theory and Projects) A to Z - RNN Architecture: ManyToMany Model Exercise 01

The video tutorial explains the many-to-many architecture of Recurrent Neural Networks (RNNs), where the input and output lengths are equal. It discusses how inputs and outputs are represented as vectors and provides examples of scenarios where this architecture is applicable. The tutorial emphasizes that while each input-output pair has equal lengths, different pairs can have varying lengths.

What does it mean for training pairs in a many-to-many RNN to have the same length but different input instances?

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In what scenarios might you apply a many-to-many architecture in recurrent neural networks?

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