Transcription of Software Engineering for Machine Learning: A Case Study
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Software Engineering for Machine Learning: A Case Study
Software Engineering for Machine Learning: A Case StudySaleema AmershiMicrosoft ResearchRedmond, WA BegelMicrosoft ResearchRedmond, WA BirdMicrosoft ResearchRedmond, WA DeLineMicrosoft ResearchRedmond, WA GallUniversity of ZurichZurich, KamarMicrosoft ResearchRedmond, WA NagappanMicrosoft ResearchRedmond, WA NushiMicrosoft ResearchRedmond, WA ZimmermannMicrosoft ResearchRedmond, WA Recent advances in Machine learning have stim-ulated widespread interest within the Information Technologysector on integrating AI capabilities into Software and goal has forced organizations to evolve their developmentprocesses. We report on a Study that we conducted on observingsoftware teams at microsoft as they develop AI-based applica-tions. We consider a nine-stage workflow process informed byprior experiences developing AI applications ( , search andNLP) and data science tools ( application diagnostics and bugreporting).
software engineering applies to machine-learning–centric components vs. previous application domains. II. BACKGROUND A. Software Engineering Processes The changing application domain trends in the software industry have influenced the evolution of the software pro-cesses practiced by teams at Microsoft. For at least a decade
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