Deep Learning - Crash Course 2023 - Program Overview

The video tutorial explains the concept of neurons and the parameters West and B, aiming to match labeled inputs to outputs. It introduces gradient descent as a method to optimize these parameters by minimizing the loss function. The tutorial then guides through implementing a Sigma Neuron class in Python, detailing methods for sigmoid and loss computation. It further explains how to compute gradient descent for parameters West and B and concludes with a method to fit the data by updating these parameters.

What are the parameters that the fit method takes in, and what is its purpose?

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Describe the process of updating the values of West and B after computing the gradients.

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