The ROC Curve, Explained

An image that shows an ROC curve, with the title "ROC Curves, Explained."

In machine learning, evaluating the performance of a model is as important as its creation. We need tools and techniques to help guarantee that the model performs well and meets the standards of our task. Enter the ROC curve – a powerful visualization designed for evaluating the performance of a machine learning classification system. This … Read more

Confusion Matrix, Explained

A Confusion Matrix, Explained, which shows a 2x2 grid of correct and incorrect classification predictions.

The confusion matrix is an important and commonly used tool in machine learning. This is particularly true of classification problems, where we build systems that predict categorical values. Because they’re used so frequently for classification problems, you need to know them, and you need to know them well. So in this blog post, I’m going … Read more

How to Use the Sklearn Logistic Regression Function

An image of a logistic regression model made with Scikit-learn, also showing a piece of Scikit-learn code.

In this tutorial, I’ll show you how to use the Sklearn Logistic Regression function to create logistic regression models in Python. I’ll quickly review what logistic regression is, explain the syntax of Sklearn LogisticRegression, and I’ll show you a step-by-step example of how to use the technique. If you need something specific, just click on … Read more

Sklearn make_classification, Explained

An image of code that uses Scikit-learn make_classification to create a binary classification dataset, and an image of a scatterplot that plots the resulting binary data.

With the rise of AI, machine learning has suddenly become very popular. Machine learning has been around for decades, but machine learning systems are becoming increasingly important in a range of fields, from healthcare, to finance, to marketing. Python, with a range of libraries for data science and ML, has arguably become the top language … Read more

How to Make a Python Perceptron from Scratch

An image that shows a Perceptron, and code to initialize a Python Perceptron.

The Perceptron stands as one of the most basic building blocks for creating neural networks, including more advanced structures like deep networks and their variants. Originally developed in the late 1950s, Perceptrons were designed to mimic the function of biological neurons. I recently wrote a blog post explaining some of the history of Perceptrons as … Read more

The 3 Data Visualization Packages You Need for Machine Learning

Obviously, AI taken off in the last year in ways that were hard for most people to predict. AI went from being a somewhat niche technical subject that nerdy guys talked about on college campuses, to being so popular that Boomer parents and grandparents are saying that “AI will change everything.” And although I think … Read more

How to do Simple EDA for Machine Learning

An old image of the Titanic in Belfast, Ireland, with the Python logo off to the upper right hand side of the image.

In this tutorial, I’ll show you how to do some simple exploratory data analysis (EDA) for a machine learning project. In this tutorial, we’ll look at the Titanic dataset, which is commonly used in machine learning tutorials, and has previously been used as a Kaggle dataset. This tutorial will really only scratch the surface. There’s … Read more