Data-science

This article explores the importance of Data Modeling as a foundational blueprint for organizing information within a business, aiding in the development of a data warehouse. It emphasizes the role of a Logical Data Model (LDM) in establishing frameworks for business intelligence and analytics, ensuring data consistency, quality, and effective communication. The article also contrasts Online Transactional Processing (OLTP) and Online Analytical Processing (OLAP) models and summarizes the transition from a Logical to a Physical Data Model (PDM) for enhanced database performance.

We delve into the intricacies of Gaussian Naive Bayes classification. The focus is on determining the probability of a data point belonging to a specific class among several, emphasizing probabilistic assessment over precise labeling. The article breaks down key concepts, from Bayesian decision theory to Bayes' theorem, and provides a step-by-step implementation using the Iris dataset.