Katherine Johnson was a trailblazing mathematician at NASA whose calculations for the Mercury and Apollo missions helped guide U.S. space exploration. Learn about her groundbreaking contributions to applied mathematics.
Learn how data science revolutionizes predictive maintenance through key techniques like regression, anomaly detection, and clustering to forecast machine failures and optimize maintenance schedules.
Discover best practices for creating clear and compelling data visualizations that communicate insights effectively.
See how hypothesis testing helps draw meaningful conclusions from data in practical scenarios.
Explore the fundamentals of Bayesian inference and how prior beliefs combine with data to form posterior conclusions.
Understand how simple linear regression models the relationship between two variables using a single predictor.
An introduction to probability theory concepts every data scientist should know.
A comparison between machine learning models and univariate time series models for predicting emergency department visit volumes, focusing on predictive accuracy.
Leveraging customer behavior through predictive modeling, the BG/NBD model offers a more accurate approach to demand forecasting in the supply chain compared to traditional time-series models.
The log-rank test is a key tool in survival analysis, commonly used to compare survival curves between groups in medical research. Learn how it works and how to interpret its results.