Understanding the Confusion Matrix for Model Evaluation & Monitoring

Understanding the Confusion Matrix for Model Evaluation & Monitoring   Anyone can build a machine learning (ML) model with a few lines of code, but building a good machine learning model is a whole other story. What do I mean by a GOOD machine learning model? It depends, but generally, you’ll evaluate your machine learning model based on some predetermined metrics that you decide to use. When it comes to building classification models, you’ll most likely use a confusion matrix and related metrics to evaluate your model. Confusion matrices are not just useful in model evaluation but also model monitoring… Read More


An Introduction to Ethics in AI

An Introduction to Ethics in AI Background of Artificial Intelligence Artificial Intelligence (AI) has been a hot topic in the twenty-first century. It’s become so prevalent that there’s a need for over a million AI engineers worldwide, YouTube created a nine-video series on AI, and Elon Musk started a company called Neuralink in response to his concerns around AI. AI has almost doubled in interest over the past five years according to Google Trends, but has been around since the 1950’s — Norbert Wiener theorized that all intelligent behavior was the result of feedback mechanisms and this very idea influenced much of… Read More


A Walkthrough of the Machine Learning Life Cycle

A Walkthrough of the Machine Learning Life Cycle   Introduction Do you have a project idea but you don’t know where to start? Or maybe you have a dataset and want to build a machine learning model, but you’re not sure how to approach it? In this article, I’m going to talk about a conceptual framework that you can use to approach any machine learning project. This framework is inspired by the theoretical framework and is very similar to all of the variations of the machine learning life cycle that you may see online. So why is a framework important?… Read More