Much of the focus in data science tends to be the application of traditional statistics techniques in more automated ways. This talk will discuss how this automation now makes it possible for data scientists to apply much more sophisticated computation to their data to achieve deeper insights and derive more value from the data.

Computational techniques originally developed for science and engineering applications can often be applied, in sometimes surprising ways, to big data applications. During the talk, we’ll see how techniques from machine learning, to image processing, to signal processing are now easy to apply.

Jon McLoone
Director of Technical Services, Communication and Strategy, Wolfram Research Europe

With over 25 years of experience working with Wolfram Technologies, Jon has helped in directing software development, system design, technical marketing, corporate policy, business strategies and much more.

Jon gives regular keynote appearances and media interviews on topics such as the Future of AI, Enterprise Computation Strategies and Education Reform, across multiple fields including healthcare, fintech and data science.

Jon holds a degree in mathematics from the University of Durham. Jon is also Co-founder and Director of Development for computerbasedmath.org, an organisation dedicated to a fundamental reform of maths education and the introduction of computational thinking.

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