Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)

A Machine Learning Project implemented from scratch which involves web scraping, data engineering, exploratory data analysis and machine learning to predict housing prices in New York Tri-State Area.

The "House Price Prediction" project focuses on predicting housing prices using machine learning techniques. By leveraging popular Python libraries such as NumPy, Pandas, Scikit-learn (sklearn), Matplotlib, Seaborn, and XGBoost, this project provides an end-to-end solution for accurate price estimation.

An example project that predicts house prices for a Kaggle competition using a Gradient Boosted Machine.

Unlocking Melbourne's housing market secrets! This project demystifies property prices by training a Random Forest model on key features. From a simple linear model to a fine-tuned powerhouse, it achieves an impressive 85% accuracy, turning data into predictive power.

Example project to predict housing pricing by using scikit, onnx and fastapi.

Building Toronto Housing dataset from scratch to predict real estate prices

Project work and Assignments for Machine learning specialization course on Coursera by University of washington

This is a regression problem to predict california housing prices.

Predict Housing Prices using Machine Learning.

No description available

Predict housing prices in Portland, Oregon for selling or buying house

This project applies basic machine learning concepts on Ames Housing dataset to predict the selling price of a new home.

Predictive Analytics project on housing price analysis using machine learning models.

I have built a Model using Random Forest Regressor of California Housing Prices Dataset to predict the price of the Houses in California.

This notebook explores the housing dataset from Kaggle to predict Sales Prices of housing using advanced regression techniques such as feature engineering and gradient boosting.

ML model trained on data from Bayut.com to predict housing prices in Dubai

Public Repo of my machine learning project to predict home prices

Predicting Boston Housing Prices using Linear Regression

Analyse a Housing Dataset of Usa for predicting housing prices for regions in the USA

简单的线性回归模型预测房价

No description available

This project analyzes and predicts housing sale price based on features such as square footage, number of bedrooms, views, locations, etc.

Linear regression modelling of the Ames housing dataset, with the goal of predicting the house sale price, as published in Towards Data Science on Medium.com

This project aims to develop a linear regression model to predict housing prices in California using the California Housing dataset. The project explores the impact of feature selection and scaling on the model's performance, with a focus on improving the accuracy of price predictions.

Machine Learning Engineer Nanodegree Project Udacity

Udacity Machine Learning Course Predicting Boston Housing Prices

Performing Regression on Housing Dataset and Predicting the house Price.

Ames Housing Price Predictor is an ML project focused on predicting housing prices in Ames, Iowa. Development spans all stages of the machine learning model lifecycle, from data exploration and cleansing, through feature engineering and model selection, to deploying a working API using FastAPI, Docker, and GCP.

A machine learning project to predict the housing price based on Kaggle Housing Prices Competition