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PRODUCTION ROBUSTNESS
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Classroom Contents
Leading Data Science Teams - A Framework to Help Guide Data Science Project Managers - Jeffrey Saltz
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- 1 Intro
- 2 INTRODUCTION
- 3 OUTLINE
- 4 THINKING ABOUT PROJECT RISKS Some possible Issues
- 5 MANAGING PROJECT RISKS Example questions to ask
- 6 KEY AREAS OF FOCUS: 1 Team Roles - The composition of team
- 7 Data Scientist uses visualizations and machine learning to aid in the understanding data. Has an overview of the end-to-end process
- 8 EXAMPLE TEAM ROLES
- 9 TEAM PROCESS The process the team uses
- 10 TEAM PROCESS: SCRUM
- 11 TEAM PROCESS: CRISP-DM
- 12 TEAM PROCESS: KANBAN
- 13 ETHICS
- 14 EXAMPLE ETHICAL QUESTIONS
- 15 HOW TO ENSURE DATA QUALITY Some key questions: • Did cleaning introduce errors?
- 16 ANALYTICS WORKFLOW EXAMPLE
- 17 MODEL MANAGEMENT
- 18 PRODUCTION ROBUSTNESS
- 19 EXAMPLE MODEL DASHBOARD
- 20 2 QUICK POLLS - PRIORITIZATION & ROLE
