Demystifying Data Science
Discover how data science, a multidisciplinary field combining statistics, computer science, and domain expertise, can drive better business decisions and outcomes.
Recent posts
Exploring Shared Nearest Neighbors (SNN) for Outlier Detection
SNN is a distance metric that enhances traditional methods like k Nearest Neighbors, especially in high-dimensional, variable-density datasets.
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.
Customer Lifetime Value: An In-Depth Exploration for Data Practitioners and Marketers
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: The First Woman to Win the Fields Medal
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.
Understanding Value at Risk (VaR) and Its Types
A detailed exploration of Value at Risk (VaR), covering its different types, methods of calculation, and applications in modern portfolio management.
Understanding the Fowlkes-Mallows Index: A Tool for Clustering and Classification Evaluation
The Fowlkes-Mallows Index is a statistical measure used for evaluating clustering and classification performance by comparing the similarity of data groupings.
Understanding Mean Time Between Failures (MTBF)
Explore the key concepts of Mean Time Between Failures (MTBF), how it is calculated, its applications, and its alternatives in system reliability.
Chi-Square Test: Testing Categorical Data
The Chi-Square Test is a powerful tool for analyzing relationships in categorical data. Learn its principles and practical applications.
Advanced Statistical Methods for Efficient A/B Testing
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.