Gaussian Processes for Time-Series Analysis in Python
Dive into Gaussian Processes for time-series analysis using Python, combining flexible modeling with Bayesian inference for trends, seasonality, and noise.
Dive into Gaussian Processes for time-series analysis using Python, combining flexible modeling with Bayesian inference for trends, seasonality, and noise.
A detailed exploration of Customer Lifetime Value (CLV) for data practitioners and marketers, including its calculation, prediction, and integration with other business data.
Maryam Mirzakhani made history as the first woman to win the Fields Medal for her groundbreaking work on the geometry of Riemann surfaces. Her contributions continue to inspire mathematicians today.
A detailed exploration of Value at Risk (VaR), covering its different types, methods of calculation, and applications in modern portfolio management.
The Fowlkes-Mallows Index is a statistical measure used for evaluating clustering and classification performance by comparing the similarity of data groupings.
Explore the key concepts of Mean Time Between Failures (MTBF), how it is calculated, its applications, and its alternatives in system reliability.
The Chi-Square Test is a powerful tool for analyzing relationships in categorical data. Learn its principles and practical applications.
An in-depth exploration of sequential testing and its application in A/B testing. Understand the statistical underpinnings, advantages, limitations, and practical implementations in R, JavaScript, and Python.
Dive into the fascinating world of pedestrian behavior through mathematical models like the Social Force Model. Learn how these models inform urban planning, crowd management, and traffic control for safer and more efficient public spaces.
Delve into how multiple linear regression and binary logistic regression handle errors. Learn about explicit and implicit error terms and their impact on model performance.