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An article detailing how to build a flexible, explainable, and algorithm-agnostic ML pipeline with MLflow, focusing on preprocessing, model training, and SHAP-based explanations.
An article discussing a simple and free way to automate data workflows using Python and GitHub Actions, written by Shaw Talebi.
Notebooks are not enough for ML at scale
The Self-Learning Path To Becoming A Data Scientist, AI or ML Engineer
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