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.

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

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.

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. 🚀📊🏡

Austrian housing market information deployed as Dash web app.

Predict Boston House Prices Using Python & Linear Regression

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.

Notebook containing Melbourne Housing Market analysis with Random Forest and Linear Regression.

In this notebook, you'll find some R code analysing a fictionnal housing market from Kaggle