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...
Main Author: | |
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Format: | eBook |
Language: | English |
Published: |
[Erscheinungsort nicht ermittelbar], Boston, MA
Data Science Salon, Safari
2019
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Edition: | 1st edition |
Subjects: | |
Online Access: | |
Collection: | O'Reilly - Collection details see MPG.ReNa |
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 |
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Item Description: | Online resource; Title from title screen (viewed September 10, 2019) |
Physical Description: | 1 video file, circa 29 min. |