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The dirty work for making intelligent products & more

Wydarzenie:
The dirty work for making intelligent products & more
Typ wydarzenia:
Spotkanie
Kategoria:
Tematyka:
Data:
18.02.2020 (wtorek)
Godzina:
18:00
Język:
angielski
Wstęp:
Bezpłatne
Miasto:
Miejsce:
High Five Two
Adres:
Pawia 9
Agenda:
  • 6:00 PM - 6:30 PM - Networking
  • 6:30 PM - 7:00 PM - Myths & Realities of Bringing Machine Learning into a Business (Catherine Williams)
  • 7:00 PM - 7:15 PM - Short break
  • 7:15 PM - 8:00 PM - The dirty work for making intelligent products (John Le)
  • 8:00 PM - 9:00 PM - Q&A, Networking
Opis:

Title: The dirty work for making intelligent products and Myths & Realities of Bringing Machine Learning into a Business.


Speaker: Catherine Williams, Qualtrics


Abstract:

Machine learning has the potential to move the needle for many businesses, but it's challenging for leaders to know where to start — and what's fact vs. fiction. We'll talk about the myths and realities of establishing a machine learning strategy, building expert teams, and delivering business outcomes, illustrated by examples from the Qualtrics iQ and beyond.


Bio:

Catherine Williams is Global Head of iQ at Qualtrics, where she oversees the group of engineers and ML researchers responsible for iQ, the set of advanced intelligent features built directly into the Qualtrics platform that make predictive intelligence and statistical analysis accessible for all. Previously she was Chief Data Scientist at Xandr, a division of AT&T, and in a previous life, spent some time as an academic mathematician.


Speaker: John Le, Qualtrics


Abstract:

We all want to bring the power of ML to our masses of customers. This talk is about the many little details that have to come together to make great intelligent products that anyone can use. Where each individual detail may look small, but the whole of what they accomplish creates an amazing experience.


Bio:

John Le is an Engineering Manager in iQ at Qualtrics, where he oversees a team making statistical analysis and prediction accessible for all. Previously he was a co-founder of Statwing, a company building an easy to use stats product.




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