Deep Learning - Deep Neural Network for Beginners Using Python - Basics of Backpropagation

The video tutorial explains backpropagation in neural networks, focusing on weights and models. It covers feedforward operations, error calculation, and the use of gradient descent to update weights and minimize errors. The tutorial also discusses the calculation of gradients and how they are used to adjust weights in the network.

Describe how weights are adjusted based on the performance of different models.

What is the prediction formula used in a simple neural network?

How do you calculate the gradient for updating weights in a neural network?