Machine Learning Articles

Rushikesh Pupale

Updated on March 19, 2025

A support vector machine is a supervised machine learning algorithm used for classification and regression tasks. Learn how it works and how to implement it in Python.

Anmol Tomar

Updated on March 14, 2025

The elbow method is a technique used to find the optimal number of clusters (K) in k-means clustering, by identifying the “elbow” point on a graph of k-values and their corresponding within-cluster sum of squares (WCSS) values.

Stephen Gossett

Updated on March 13, 2025

The model is learning new tricks everywhere from recommender systems to Minecraft.

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.

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.

Noah Topper

Updated on March 10, 2025

Beam search is an approximate search algorithm that only remembers the top possible solutions to determine the best one. Here’s how it works, its applications, advantages, potential limitations and an example of beam search in action.

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.

Edmond Yip

Updated on March 04, 2025

A variational autoencoder (VAE) is a generative AI model that is used to improve the quality of images generated by tools like Stable Diffusion. Here are some applications of VAEs, how to use a VAE in Stable Diffusion and the pros and cons of VAEs.

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.