Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in RNN: Equations Exercise

The video tutorial discusses the parameter matrices W and the hidden state vector A, which has 10 elements. It explains the input vector X with 20 elements and how Y is computed using these vectors and matrices. The tutorial explores the necessary sizes and orders of matrices for computing Y and how to combine vectors and matrices to simplify the equation, resulting in a new vector Z.

What new insight or understanding did you gain from this video?

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