Data and AI are essential across all business areas. There is a broad and growing spectrum: from Machine Learning to Neural Networks, from Chatbots to AI in IT Operations…
In this session we will give an introduction to Mathematical Optimization. The aim of many Data Science projects is to generate value by discovering new insights to support better business decisions. However, exactly how to make these decisions in an optimal fashion is often far from obvious. At the same time, poor decisions can eliminate any value added by Data Science very quickly.
In such cases, Mathematical Optimization can help by offering better decisions quickly and consistently while considering a multitude of factors like predictions of demand and supply of raw material. We invite you to explore together how this fascinating technology works, what it can do, and the advantages it brings.
Sebastian Fink joined IBM as a Consultant for Advanced Analytics & Optimization in 2010 after graduating from Darmstadts University of Technology. He worked on many data science projects across all industries before moving to a Technical Sales role for Decision Optimization in 2016. In this capacity, he was involved in numerous customer engagements centered on Data Science in general and optimization in particular.
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This webinar will be livestreamed on Crowdcast.
➡ Please register in advance, if you can: https://www.crowdcast.io/e/data-ai-series-mathematical-optimization
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Data & AI Demystified – Your Path to AI.
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In case you missed any of the previous sessions in our series and are interested to learn more, you can find the replays here: https://ibm.biz/aiseries2021