/Kaggle-House-Prices-Advanced-Regression-Techniques

The main objective of this competition is to predict house sales prices using Machine Learning algorithms and practice feature engineering, RFs, and gradient boosting.

Primary LanguageJupyter Notebook

House Prices: Advanced Regression Techniques - Full Guide

This is one of the best competitions for beginners on Kaggle. The main objective of this competition is to build a regression model in order to predict house sales prices using Machine Learning algorithms while practicing feature engineering, RFs, and gradient boosting.

This project was carried out as part of the training of engineers at Tunisia Polytechnic School under the module "Data Analysis" taught in second year.

Project Link

https://www.kaggle.com/c/house-prices-advanced-regression-techniques

House Prices

Necessary Skills

  • Python programming language
  • Machine Learning basics
  • Feature engineering

Instructions

  1. Import libraries
  2. Load the data
  3. Clean the data
  4. Train the data
  5. Make & Submit prediction