Deep Learning - Deep Neural Network for Beginners Using Python - Feed Forward for DEEP Net

The video tutorial explains the criteria for a neural network to be considered deep, focusing on the number of hidden layers. It details the matrix dimensions for weights in different layers and describes the feedforward process to compute the output, Y hat, using sigmoid functions. Finally, it introduces the concept of error minimization in neural networks.

How does the number of iterations affect the calculation of Y hat in a deep neural network?

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What is the next step after calculating the output Y hat in a neural network?

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Discuss the importance of minimizing error in the context of neural networks.

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