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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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Detalles Bibliográficos
Autor principal: Salon, Data (Autor, VerfasserIn.)
Autor Corporativo: Safari, an O'Reilly Media Company (Contribuidor, MitwirkendeR.)
Formato: Video
Idioma:Inglés
Publicado: [Erscheinungsort nicht ermittelbar] : Data Science Salon, 2019
Edición:1st edition.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
Sumario: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.
Notas:Online resource; Title from title screen (viewed September 10, 2019).
Descripción Física:1 online resource (1 video file, circa 29 min.)