getindata/quickstart-ml-blueprints
Data science project development best practices and state of the art open-source tooling forged into a set of solved ML use cases to serve as blueprints for efficient prototyping.
This project provides pre-built, production-ready templates for common machine learning problems like forecasting sales, building recommender systems, or classifying customer behavior. It takes your raw data, applies best practices for data science project structure, and outputs a complete, well-tested machine learning solution. Data scientists and machine learning engineers can use these blueprints to quickly develop high-quality ML applications.
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Use this if you are a data scientist or ML engineer looking to jumpstart a new project with a proven structure and best-in-class open-source tooling, aiming for faster prototyping and high-quality production code.
Not ideal if you are looking for a low-code/no-code ML platform or a simple Python library for specific ML algorithms, as this focuses on full project solutions and development best practices.
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Jupyter Notebook
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Last pushed
Jun 28, 2023
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