An introduction to Docker and GitHub Actions for ML app.
A methodical and reproducible research, workflow is the cornerstone for scientific research practice. Workflows are often misunderstood; the terms workflow and pipeline are often used interchangeably. Workflows and pipelines will be explored by examining the approach to answering scientific questions and the computational steps that are typically undertaken to aid answering those questions. The three stages of scientific workflow will also be discussed. The first stage includes processing, interrogating, and screening data. This stage is followed by focussing attention on promising avenues, and when satisfied, the output is assembled for review and evaluation as part of the final stage. These workflow stages are often iterative; feedback is passed back to the first stage to aid workflow refinement and improvement.
Pre-requisites: Some understanding of software engineering concepts and terms is required.
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