Michelle Gregory
SVP of Data Science

AI / Augmented / Automated Machine Learning – Techniques and Applications

There is a lot of visioning going on around AI/Augmented/Automated machine learning as well as some first good specialist topic examples. But what are the techniques being used and can they be applied to day-to-day tasks?

Operationalizing Data & Machine Learning

The reality of industrial AI is that success mostly relies on functions that have nothing to do with sophisticated algorithms, and all to do with product operationalisation. Operationalisation ranges from defining what problem to solve (market understanding, customer workflows, product requirements) to verifying that what was built actually solves it (quality assurance, product analytics, customer success) to ensuring that the result is a viable product (business intelligence, marketing and operations).

Yann-Landrin-Schweitzer
Sr. Director, Machine Learning

Brian O'Neill
Product Designer and UX Consultant

Is empathy the missing ingredient in your next data product?

In this interactive session, Brian will share some UX & design strategies that can help leaders create more engaging, useful, and usable analytics software that is rooted in what users and stakeholders actually need.