This note looks at the lessons learned from hundreds of inquiries and a recent data science survey to outline some best practices for driving machine learning projects. Our findings are geared to guide data and analytics leaders, but should be applicable for other stakeholders too.
- Create a Portfolio of AI and ML Ideas
- Evaluate Ideas in Terms of ROI and Risks
- Launch, Run and Deploy ML Projects
- Further Improving the Data Science Capabilities of the Organization
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