Presentation Quality Checklist¶

Before presenting your machine learning project to stakeholders, check these boxes.

The Checklist¶

The "So What" is on Slide 1: Is the core business value stated immediately?
No Raw Code: Have you removed all Python snippets from the main deck? (Put them in the appendix).
No Confusion Matrices: If you must show performance, translate it into monetary value, time saved, or user satisfaction.
Baseline Comparison: Did you clearly state what the model is beating? (e.g., replacing manual sorting).
Visual Clarity: Do all graphs have large titles, labelled axes, and a clear takeaway sentence printed directly on the slide?
Limitations Acknowledged: Did you briefly explain where the model struggles so nobody discovers it mid-meeting?
Clear Next Steps: Are you asking for a specific decision (e.g., "approve budget for A/B test", "sign off on API deployment")?

KSB	Description	How This Addresses It
S5	Deployment, value assessment, and ROI	Translating model performance into business impact
S6	Communicate through storytelling and visualisation	Presenting ML results to non-technical stakeholders
B4	Consideration of organisational goals	Framing technical results in terms of business objectives
B1	Inquisitive approach	Exploring creative ways to explain model behaviour