IA-AirBnB
Data science pipeline for Airbnb price prediction using Lyon and Paris data, with preprocessing, analysis and linear regression models.
Stack
- Python
- Pandas
- Scikit-learn
- Linear Regression
Context
IA-AirBnB is a data project focused on turning raw Airbnb datasets from Lyon and Paris into a model-ready workflow.
Problem
The project explores how structured accommodation data can be cleaned, analyzed and used to predict prices with a simple, explainable baseline.
Solution
The workflow covers preprocessing, exploratory analysis, outlier handling, train/test split and linear regression modeling.
Architecture
The architecture is a notebook/script-style data pipeline: load files, clean data, build features, train a baseline model and prepare evaluation outputs.
Features
The verified scope is the data workflow described in the repository.
Result
The project demonstrates an end-to-end data workflow; no model metric is published here without repository evidence.
Does this project speak to you?
I'm available for a permanent role and for freelance missions. Let's talk about your team or your project.