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.

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