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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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Bibliographic Details
Main Author: Salon, Data (Author, VerfasserIn.)
Corporate Author: Safari, an O'Reilly Media Company (Contributor, MitwirkendeR.)
Format: Video
Language:Inglés
Published: [Erscheinungsort nicht ermittelbar] : Data Science Salon, 2019
Edition:1st edition.
Online Access:Texto completo (Requiere registro previo con correo institucional)
Description
Summary: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.
Item Description:Online resource; Title from title screen (viewed September 10, 2019).
Physical Description:1 online resource (1 video file, circa 29 min.)