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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 ...

Amid the wave of the digital age, advanced technologies such as big data, artificial intelligence, and cloud computing are driving precise analysis and forecasting across various fields. This paper ...

This project implements Multiple Linear Regression using Gradient Descent in pure Python (without external libraries like NumPy or Scikit-learn). The goal is to train a model that predicts an output ...

Background: The aim of the present study was to establish a predictive model to predict the peritoneal cancer index (PCI) preoperatively in patients with pseudomyxoma peritonei (PMP). Conclusion: This ...

Using machine learning to forecast maintenance readiness at the frontline unit level. The Army’s current model to determine future equipment readiness levels falls short of enabling command ...

Abstract: Regression analysis, a stalwart in statistical methodology, offers a robust framework for predicting outcomes based on historical data. It hinges on the premise that by scrutinizing past ...

This repository contains an implementation of a multiple linear regression model for predictive analysis. The model explores the relationship between multiple independent variables and a dependent ...