Introduction to Machine Learning: K Means

Welcome to our fourth installment on Machine Learning. In this module we’re going to cover K-Means. K-Means is a clustering algorithm based on the hyperparameter “K” which dictates how many clusters there will be. A hyperparameter is just a parameter that we can adjust. Each cluster has a “centroid” or a central point that willContinue reading “Introduction to Machine Learning: K Means”

Introduction to Machine Learning: Logistic Regression

Ping! Is this another spam email? Or is it legit? How does your email spam filter tell? Perhaps it uses a simple machine learning technique. In this post, we’re going to learn about what it is and how we can create a Python logistic regression program. We will cover: Machine Learning: What is Logistic Regression?Continue reading “Introduction to Machine Learning: Logistic Regression”

Introduction to Machine Learning: Linear Regression

Linear Regression is a technique to create a linear equation given a dataset. We use this when we expect to have a linear correlation, perhaps something like square footage of an apartment compared to rent price. First, I’m going to show you an example of how linear regression works via sklearn and then we’ll buildContinue reading “Introduction to Machine Learning: Linear Regression”