How to Test Machine Learning Code and Systems
Read OriginalThis technical article explains the differences between traditional software testing and machine learning testing. It details a workflow for ML testing, including pre-train tests for code logic, post-train tests for model behavior, and performance evaluation. The guide uses a numpy DecisionTree implementation and the Titanic dataset for practical examples, with code available in a linked GitHub repository.
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