Deep Learning - Deep Neural Network for Beginners Using Python - Gradient Step

The video tutorial explains how to update weights using gradient descent, focusing on the derivative of the cross-entropy error function. It simplifies calculus concepts for beginners and derives the equation for weight updates. The tutorial also covers updating biases and concludes with the application of these concepts in logistic regression, a foundational algorithm for deep neural networks.

How is the bias updated in the gradient descent algorithm?

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What is logistic regression and how does it relate to gradient descent?

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