Building a Classifier from Scratch

Implementing Gradient Descent for Classification

The math is similar to Linear Regression, but we use the Sigmoid gradient.

Steps:

1. Calculate linear output: z = weight * X + bias
2. Apply Sigmoid: predictions = sigmoid(z)
3. Calculate Error: error = predictions - y
4. Calculate Gradients & Update weights.