Deep Learning - Crash Course 2023 - Loss Function and Parameter Update

The video tutorial explains the perceptron model, focusing on training neural networks by adjusting weights and biases based on a loss function. It provides an example of loss calculation and describes the process of updating parameters using a learning algorithm. The tutorial also covers the logic behind parameter updates, emphasizing the importance of correctly classifying input data.

What is the role of the learning algorithm in updating the parameters of the perceptron model?

How does the perceptron model handle misclassified inputs during training?

Discuss the mathematical reasoning behind adding or subtracting the input X from the weights.