Solving Logistic Regression with Newton's Method
In this post we introduce Newton’s Method, and how it can be used to solve Logistic Regression. Logistic Regression introduces the concept of the Log-Likelihood of... »
Gradient Descent: High Learning Rates & Divergence
We’ve explored gradient descent, but we haven’t talked about learning rates, and how these hyperparameters are the key differentiators between convergence, and divergence. More specifically, let’s... »
The Gradient: A Visual Descent
In this post I aim to visually, mathematically and programatically explain the gradient, and how its understanding is crucial for gradient descent. For those unfamiliar, gradient... »