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Literate Statistical Programming for Reproducible Data Science

Offered By: Toronto Machine Learning Series (TMLS) via YouTube

Tags

Data Science Courses Oracle Courses Statistical Analysis Courses Scientific Method Courses Auditing Courses

Course Description

Overview

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Explore the concept of Literate Statistical Programming (LSP) in this 46-minute conference talk by John Peach, Principal Data Scientist at Oracle, presented at the Toronto Machine Learning Series. Discover how LSP addresses the reproducibility crisis in science and data science by binding analysis code to result interpretation. Learn about the philosophy, tooling, and workflow of LSP, which has been successfully applied to both small-scale datasets in startups and massive-scale problems at Oracle and Amazon Alexa. Gain insights into creating a reproducible, auditable, and flexible data science workflow that allows for rapid iteration and experimentation. Understand the guiding principles of LSP and how to transition from an ad-hoc approach to a more structured and efficient methodology for data science projects.

Syllabus

John Peach - Literate Statistical Programming


Taught by

Toronto Machine Learning Series (TMLS)

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