Data Science Articles

Stephen Gossett

Updated on March 13, 2025

Gender data can be valuable for a variety of reasons. But before you ask, consider why you’re asking, and how you frame the question.

Valentina Alto

Updated on March 13, 2025

Ordinary Least Squares (OLS) regression is a technique used in linear regression to minimize the sum of squared differences between observed and predicted values, and obtain a straight line as close as possible to your data points.

Sadrach Pierre

Updated on March 12, 2025

A step-by-step tutorial on how to heapify data in a tree data structure, including visuals and example code.

Mae Rice

Updated on March 12, 2025

We asked three machine learning engineers how they got into their roles and how newcomers can follow in their footsteps.

Shesh Narayan Gupta

Updated on March 11, 2025

Our expert explains everything you need to know about installing DeepSeek locally on both Mac and PC. Learn more.

Carla Martins

Updated on March 10, 2025

Gaussian Naive Bayes is a classification technique used in machine learning based on the probabilistic approach and Gaussian distribution. Here’s a deep dive on how to use it in Scikit-Learn.

KSV Muralidhar

Updated on March 05, 2025

Adjusted R-squared is a modified version of R-squared that adjusts for predictors that do not contribute to predictive accuracy in a regression model. It can be a reliable measure of goodness of fit for multiple regression problems.

Lynn Kwong

Updated on March 03, 2025

Asyncio is a Python library that allows us to write concurrent code using the async/await syntax. Learn how to use this library to write asynchronous code.

Jenny Lyons-Cunha

Updated on February 27, 2025

Federated learning is a technique for training an AI model across a network of devices without having to share data with a central server. Here’s a closer look at how it works, its types, applications, challenges and benefits.

Shesh Narayan Gupta

Updated on February 26, 2025

Root mean square propagation (RMSProp) is an adaptive learning rate optimization algorithm designed to improve training and convergence speed in deep learning models.