Segment the Chicago's housing market and determine the main factor's influencing the housing price.

This repository contains a machine learning algorithm that trains a model to predict house prices based on specified features of the homes, using the California Housing Dataset.

🔍 📈 Exploratory data analysis and Sklearn algorithm test harness for QA Datascience Summative assignment.

Dallas house price Analysis

This repository contains a machine learning algorithm that trains a Random Forest model to predict house prices based on specified features of the homes, using the California Housing Dataset. The dataset used to train and evaluate the Random Forest model to predict median housing prices.

An analysis of factors that influence housing prices in King County, WA

This project employs linear regression to predict property prices based on key features. Through thorough data cleaning, preprocessing, and feature engineering, the model is fine-tuned for accuracy. With insights from exploratory data analysis, the model offers reliable estimates, aiding stakeholders in informed decision-making.

An analysis of house prices in Beijing

house price analysis

This repository uses a simple linear regression to predict house prices in US $ based upon areas in sq ft.