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Literate Statistical Programming is not Just About Reproducibility /

Presented by John Peach, Sr Data Scientist at Amazon Alexa Science is facing a crisis around reproducibility and data science is not immune. Literate Statistical Programming is a workflow that binds the code used in an analysis to the interpretation of the results. While this creates reproducibility...

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Détails bibliographiques
Auteur principal: Salon, Data (Auteur, VerfasserIn.)
Collectivité auteur: Safari, an O'Reilly Media Company (Collaborateur, MitwirkendeR.)
Format: Vidéo
Langue:Inglés
Publié: [Erscheinungsort nicht ermittelbar] : Data Science Salon, 2019
Édition:1st edition.
Accès en ligne:Texto completo (Requiere registro previo con correo institucional)
Description
Résumé:Presented by John Peach, Sr Data Scientist at Amazon Alexa Science is facing a crisis around reproducibility and data science is not immune. Literate Statistical Programming is a workflow that binds the code used in an analysis to the interpretation of the results. While this creates reproducibility it also addresses issues around, auditing, re-usability and allows for rapid iteration and experimentation. This talk will describe a workflow that I have successfully used on small-scale data-sets in start-ups and on Amazon-scale problems in my work on Alexa. The talk will cover the tooling, workflow, and the philosophy you need to master Literate Statistical Programming.
Description:Online resource; Title from title screen (viewed September 10, 2019).
Description matérielle:1 online resource (1 video file, circa 29 min.)