These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.

This repository contains comprehensive implementations and solutions for statistical analysis, data science methodologies, and computational mathematics assignments. Each assignment demonstrates ...

The bregr package provides a streamlined, modular workflow for batch regression modeling. The process begins with installation and initialization, followed by core modeling steps such as setting ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

🔸 Predicting House Prices with Linear Regression 🔸 This project predicts house prices using Linear Regression based on key features like square footage, bedrooms, bathrooms, lot size, and ...

ABSTRACT: Nowadays, understanding and predicting revenue trends is highly competitive, in the food and beverage industry. It can be difficult to determine which aspects of everyday operations have the ...

Department of Mechanical Engineering, Stanford University, Stanford, California 94305, United States Precourt Institute for Energy, Woods Institute for the Environment, and Doerr School of ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

Abstract: Linear regression and its variants have achieved considerable success in image classification. However, those methods still encounter two challenges when dealing with hyperspectral image ...

In this video, we will implement Multiple Linear Regression in Python from Scratch on a Real World House Price dataset. We will not use built-in model, but we will make our own model. This can be a ...