Machine learning Regression problem with easy understandable solutions

This is a regression problem to predict california housing prices.

It is a regression problem, where given the set of features, we need to predict the transaction price of the house.

This is a machine learning web application built with Flask that predicts house prices in Lahore. It uses an XGBoost model trained on custom data and a clean frontend with HTML, CSS, and JavaScript.

Automated Essay Scoring as NLP, regression problem.

Detailed industry specific framework to solve Machine Learning Problem

Predict car prices and investigate effects of varying parameters

Based on the features of the diamond this ML model, predict the estimated price of the diamond. Accuracy is around 95.6%

🏡 Predict California house prices using machine learning techniques like Linear Regression and Random Forest for accurate median value estimates.