Find out how to build trust in your AI apps from our MCubed web lecture this week

Think explainability and accuracy are mutually exclusive? Think again!

Special series You have collected all the data, trained the best possible model, and built the most brilliant application, yet your potential users' distrust of AI means uptake is falling short of expectations.

Or you are working in, say, finance, and just found the perfect AI solution to your fraud problem, though you can’t seem to get your team onboard because no one is sure whether it will be compatible with upcoming legislation.

Adding explainability to your processes may go a long way to help you in both cases, which is why the third episode in our free MCubed web lecture series on practical machine learning will dive into the world of Explainable AI (XAI). On November 4 at 1100 GMT (1200 CEST), Napier’s Chief Data Scientist Dr Janet Bastiman will show you how explainability can be used to build trust and future-proof systems, while dispelling some of the myths you will likely have already encountered.

As a practitioner in the highly regulated field of finance herself, Dr Bastiman will provide you with insight into today's regulations and industry trends to help clarify what can and should be done. She’ll also present some case studies to illustrate when and how to incorporate XAI measures to make sure too much openness won’t backfire and lead to bad actors gaming your systems.


Join our MCubed web lecture this week to find out how to get machine learning into production


With more than 20 years of experience in data science, Dr Bastiman is more than familiar with the peculiarities of sectors such as telecommunications, marketing, and finance, and knows what’s important for startups and established businesses when it comes to implementing and improving their AI offerings. She’s also an avid proponent for testing in ML, a committee member for the Royal Statistical Society's Data Science Section, and holds degrees in molecular biochemistry and mathematics with a PhD in computational neuroscience.

So block off your calendar for 1100 GMT on November 4, and join us for a free hour of machine-learning news and explainability – we’re really looking forward to seeing you there.

If you sign up, we’ll even send you a reminder on the day. Maybe it inspires you to look deeper into the topic or help you with some question you’ve had for a while. Speaking of which: we’re always thankful for topic proposals to make the MCubed web series really useful, so let us know if you have any ML-related problems and we’ll investigate it in an upcoming episode. ®

PS: We're planning on running an MCubed online conference about machine learning in December – see here for more information.

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