Reproducible Data Science with Machine Learning

Explore the fundamentals of reproducible data science and machine learning in this 26-minute video from Microsoft. Learn how to set up a development workflow that enables explanation of AI algorithm decisions years after implementation. Discover the importance of reproducible research, development, and deployment using modern notebook environments like Azure ML Compute Instances. Follow along as Rafal Lukawiecki, an experienced data scientist, demonstrates a reproducible workflow using RStudio and RMarkdown, both locally and in an Azure ML Compute Instance. Gain insights into the differences between modeling, exploration, and traditional software development, and understand the steps necessary for creating a reproducible workflow in data science projects.

] Learn reproducible research with Rafal Lukawiecki.
] Modelling and exploration vs software development.
] Steps to a reproducible workflow.
] Demo: Workflow using RStudio and RMarkdown running locally.
] Demo: RMarkdown notebooks in an Azure ML Compute Instance.