Provides an end-to-end pipeline for real estate market analysis and predictive modeling, encompassing data collection, transformation, visualization, and machine learning.
InmoPipeline is a comprehensive end-to-end data engineering and data science project designed for the Colombian real estate market. It integrates automated web scraping, robust ETL processes, and efficient data warehousing with DuckDB. The project includes extensive data analysis, interactive dashboards built with Streamlit, and a powerful Random Forest machine learning model for property price prediction. The solution is deployed as a REST API using FastAPI and features intelligent automation workflows via n8n, demonstrating a full data product lifecycle from ingestion to intelligent querying.