Machine learning models degrade over time due to model drift, which includes data drift, concept drift, and feature drift. Learn how to detect, measure, and mitigate these challenges.
This article delves into mathematical models of inequality, focusing on the Lorenz curve and Gini coefficient to measure and interpret economic disparities.
Machine learning is often seen as a new frontier, but its roots lie firmly in traditional statistical methods. This article explores how statistical techniques underpin key machine learning algorithms, highlighting their interconnectedness.
Let’s examine why multiple imputation, despite being popular, may not be as robust or interpretable as it’s often considered. Is there a better approach?
AUC-ROC and Gini are popular metrics for evaluating binary classifiers, but they can be misleading on imbalanced datasets. Discover why AUC-PR, with its focus on Precision and Recall, offers a better evaluation for handling rare events.
Splines are powerful tools for modeling complex, nonlinear relationships in data. In this article, we’ll explore what splines are, how they work, and how they are used in data analysis, statistics, and machine learning.
Explore the differences between the Shapiro-Wilk and Anderson-Darling tests, two common methods for testing normality, and how sample size and distribution affect their performance.
Hypatia of Alexandria is recognized as the first known female mathematician. This article explores her contributions to geometry and astronomy, her philosophical influence, and her tragic death.
Dive into the world of calculus, where derivatives and integrals are used to analyze change and calculate areas under curves. Learn about these fundamental tools and their wide-ranging applications.
Kurt Gödel revolutionized the world of mathematical logic with his incompleteness theorems, reshaping our understanding of the limits of formal systems. Learn about his life, work, and lasting legacy in the foundations of mathematics.
