Context
IA-AirBnB is a data project focused on turning raw Airbnb datasets from Lyon and Paris into a model-ready workflow.
Data project
Python
Pandas
Scikit-learn
Linear Regression
Project
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
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.
Screenshots
The repository is the primary artifact for notebook, script and export details.