R is regaining attention in 2026, especially in statistics-heavy and research-focused data science work.Python still leads in ...

Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from Scratch. We will not use any build in models, but we will understand the code ...

Air-quality analysis of scrap-tire animal singeing sites in Ghana—PM2.5/PM10/CO/SO₂/VOCs—using LME, GAM, and quantile models with WHO guideline checks.

In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...

ABSTRACT: Accurate forecasting of the system marginal price (SMP) is crucial to improve demand-side management and optimize power generation scheduling. However, predicting the SMP is challenging due ...

This project explores two different investigation using methods of machine learning and hybrid approach to predict the peak energy consumption in Ireland and energy production in Portugal based on ...

Abstract: The optimal utilization of electrical energy is becoming increasingly necessary due to the rapid growth in the population. Several techniques have been designed to ensure judicious use of ...

Implement Linear Regression in Python from Scratch ! In this video, we will implement linear regression in python from scratch. We will not use any build in models, but we will understand the code ...

Abstract: Machine learning is transforming every sector of today’s world. By forecasting or forecasting sales, one can maximize the profits of business-to-consumer (B2C) models involving retail chains ...