Industrial ML – Overview of the Technologies Available for Machine Learning
summary
A survey of distributed, horizontally scalable Python machine-learning pipelines, covering motivations, technologies, best practices and caveats. It focuses on whether the presentation provides concrete artifacts: pipeline diagrams with components and flow, named libraries/schedulers/infrastructure, measurable benchmarks or cost figures, and a built-system postmortem showing failures and fixes.
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chapters (6)
- 0:00Industrial ML overview
- 5:33ML pipeline tech
- 15:26Data prep sources
- 25:21Deployment & scaling
- 35:07Case studies lessons
- 40:51Future trends & Q&A
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