unnati-xyz/scalable-data-science-platform
Content for architecting a data science platform for products using Luigi, Spark & Flask.
This project helps data science teams move their experimental machine learning solutions from a local machine into a reliable, automated production environment. It provides a blueprint and tools to create a robust data pipeline, transforming raw data into features, training machine learning models, and deploying them as predictive APIs. Data scientists, machine learning engineers, and platform architects looking to operationalize their models would use this.
163 stars. No commits in the last 6 months.
Use this if you need to build a complete, scalable data science platform that automates data engineering, machine learning model training, and API deployment.
Not ideal if you are solely focused on prototyping models on a local machine and do not need to scale or deploy them in a production setting.
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163
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Language
Jupyter Notebook
License
MIT
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Last pushed
Jan 27, 2020
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