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.

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.

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

Austrian housing market information deployed as Dash web app.

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.

Predict Boston House Prices Using Python & Linear Regression

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

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