Deep Learning - Deep Neural Network for Beginners Using Python - Final Project Part 3

The video tutorial covers the implementation of a neural network, focusing on the sigmoid function and its derivative, backpropagation, error calculation, and weight updates. It explains the process of training a neural network, including the addition of biases and the use of numpy for matrix operations. The tutorial concludes with the implementation of a predict function, emphasizing the flexibility of the code to handle multiple layers and neurons.

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