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Explore real-time data science in this 32-minute conference talk by Caltech PhD Chip Kent. Discover why real-time analytics are crucial, learn how to build effective systems, and understand where real-time data resides. Delve into design patterns that simplify writing, testing, running, and reproducing analytics. Gain insights from Kent's extensive experience in quantitative problem-solving across fields like investing, big data, quantum mechanics, and nuclear weapons simulations. Benefit from his expertise in technical project management, software development, and research as he makes complex concepts accessible and practical for data scientists and AI practitioners.
Syllabus
- Introductions
- Scope of this talk
- Outline
- Why real-time?
- Build Real-Time Data Science Systems
- Where real-time data moves and lives
- Design Patterns
- Make it easy to write, test, run, and reproduce your analytics
- Review
- Questions?
Taught by
Open Data Science