Automated ML pipeline with Python, Docker, Luigi, SciKit-Learn and Pandas to predict wine quality ratings
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Updated
May 30, 2020 - Jupyter Notebook
Automated ML pipeline with Python, Docker, Luigi, SciKit-Learn and Pandas to predict wine quality ratings
pipecutter provides a few tools for luigi such that it works better with data science libraries and environments such as pandas, scikit-learn, and Jupyter notebooks.
Contiene la presentación del proyecto de datos realizado a propósito de la materia "Data Product Architecture": 1) Producto de datos funcional: Video de corrida final del producto de datos; 2) Presentación de "front"; 3) Entrega de documento final en repositorio; 4) Último commit del proyecto
This repository contains an ETL (Extract, Transform, Load) pipeline implemented using Luigi, a Python package for building data pipelines. The pipeline extracts data from a CSV file hosted on a GitHub repository, performs some cleaning and transformation steps, and then loads the data into a SQLite database table.
Universal Luigi ETL pipeline. Validates data received from external sources. Extracts, transforms them and lands.
This repository is based on scraping data from a static website through Luigi. This was created to display my ability to utilize the Luigi pipeline to automatically collect data and other tasks.
Pycon 2017- Creating ETL tasks with Luigi package
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