Eugene Yan 9/6/2020

How to Test Machine Learning Code and Systems

Read Original

This 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.

How to Test Machine Learning Code and Systems

Comments

No comments yet

Be the first to share your thoughts!

Browser Extension

Get instant access to AllDevBlogs from your browser