housing-market-analysis

This project utilizes Python visualizations packages, such as Plotly Express, HVPlot and PyPlot/Matplotlib to create an interactive dashboard exploring the San Francisco real estate housing market. Uses MapBox API.

Zillow Scraper gets you Zillow data ⚡ fast, 🎯 100% accurate and 🔍 ridiculously detailed — as clean JSON. Use it to your heart's content with 1,000 free calls/month ❤️

Choice-Based Conjoint Analysis, Multinomial Logit Model, Multinomial Logit Model with random coefficients

🏙️ 2buyornot2buy: The Parker Luxury Condo Buy Signal Machine Learning and In-Depth Financial Analysis. Turning a rainy day from angst to analytical joy. This is what happens when you approach real-world life decisions analytically, you know, just for fun.

We are required to build a regression model using regularisation in order to predict the actual value of the prospective properties and decide whether to invest in them or not. The company wants to know: 1. Which variables are significant in predicting the price of a house, and 2. How well those variables describe the price of a house.

An Analytics project utilizing housing market data sourced from the Dutch website Funda.

Detect U.S. housing market bubbles using macroeconomic signals. Forecast HPI, score speculative risk, and visualize insights using a fully modular, cloud-native GCP pipeline.

Full-stack pipeline to detect U.S. housing market bubbles and forecast price trends. Merges 6+ macroeconomic datasets in Snowflake to compute risk scores and price predictions using walk-forward ML models. Deployed with Streamlit for interactive insights.

This repository operationalizes a county-level housing intelligence framework for Ireland, combining forecasting, explainable machine learning, and scenario-based demand planning to support evidence-based policy and resource allocation.

Austrian housing market information deployed as Dash web app.

house price prediction using machine learning with xgboost to estimate property values from structured housing features and engineered variables.

HabitaSense is an open-source AI housing market analysis specification that evaluates listings, pricing, sales, rentals, appraisals, property records, and financial risks to identify fair values, inflated prices, anomalies, fraud indicators, and significant market opportunities.

real estate listings scraper

Swiss real estate data extractor

Predict house prices for the next five years across all English local authorities.

This repo contains all materials necessary for the Data Science Tools 1 final project/presentation. This project is based on median household income vs typical housing price based on region.

Danish real estate data extractor

House Price Prediction is a machine learning project that analyzes real estate data to predict house prices based on various features like location, size, and amenities. It involves data preprocessing, exploratory data analysis (EDA), feature engineering, and model training using regression algorithms to provide accurate price estimates. 🚀📊🏡

99acres real estate data