Objective Business problem Approach Key findings Recommendations Summary This dataset serves as a valuable resource for identifying trends, assessing company practices, and informing policy decis...

Summary This algorithm performs classification according to Bayes Theorem. The model assisgns a sample to the class with the largest conditional probability. Inputs Numerical Categorical ...

What is normalization? Normalization is a series of steps that convert a flat or poorly structured table into multiple related tables, following standard normal forms (1NF to 3NF and beyond). ...

Summary Regression algorithm that applies regularization and feature selection to deal with overfitted1 data. The method uses L1 regularization2. Inputs Numerical Categorical Preprocessin...

This is the schedule for the current and future data analysis projects. This page is constantly updated on the progress of the projects. Projects are calculated on hours end-to-end worked for ea...

Purpose Effective database design is crucial for building reliable, efficient, and scalable data systems. It involves steps like requirements analysis, conceptual and logical modeling, normalizati...

Summary Recency Frequency Monetary analysis is a marketing technique used to analyze and segment customers based on three key factors: Recency, Frequency, and Monetary. This model helps business...

Objective Business problem Approach Key findings Recommendations Information about the dataset. This is a retailer of scale models of classic cars. The database contains typical business data ...

Techniques and Methods in How to Detect Outliers. Anomalies and outliers generate big issues when training machine learning algorithms or when we are applying statistical techniques. Outliers are ...

Parametric and Non-parametric Models in Machine Learning Machine learning can be briefed as learning a function (f) that maps input variables (X) and the following results are given in output vari...