evaluation metrics

Adjusted R-Squared: Why, When, and How to Use It

Adjusted R-squared is one of those metrics that shows up early in regression, but it often feels like a small […]

When you train a regression model, you usually want to answer a simple question: How well does this model explain

Imagine you’re teaching a robot to write poetry. You give it a prompt, and it generates a poem. But how

Clustering is an unsupervised ML that aims to categorize a set of objects into groups based on similarity. The core

Anomaly detection, also known as outlier detection, aims at identifying instances that deviate significantly from the norm within a dataset.

Time series forecasting is a statistical technique used to predict future values based on previously observed values, specifically in a

Large Concept Models (LCMs) [paper] represent a significant evolution in NLP. Instead of focusing on individual words or subword tokens,