All work
Speaking
Google Developer Student Clubs
Invited to speak on machine learning for personalised mental health intervention.
- Invited talk on ML for personalised therapeutic intervention
- Built the supporting analytics in Power BI
My argument was that the model is the easy part. Mental health data is small, deeply personal, and collected under conditions that break most of the assumptions you get taught. Anyone can fit a classifier. Knowing whether you are allowed to believe it is the skill.
I built the supporting analytics in Power BI so the claims were something the room could look at rather than take on my word. That felt important given what I was arguing.
Tools & methods
- Machine learning
- Power BI
- Public speaking