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How math can help optimize business and life

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In this presentation, AIMS Data Scientist and Theoretical Physicist Alessandra Cagnazzo discusses what's really behind machine learning. In her session "The Optimal Life" she talks about how mathematics can be applied to optimize in business, and life in general.

Published in: Science
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How math can help optimize business and life

  1. 1. The optimal life Can math help us optimise our business and life? Alessandra Cagnazzo AIMS Data Scientist
  2. 2. What do different group of people consider optimisation? Theoretical physicists Experimental physicists (a.k.a. scientist that have to deal with NICE(ish) DATA) Data scientists (a.k.a. “there is 38% possibility that that is a picture of my mum, 32% possibility that is a picture of the Pope, but also 30% possibility that that is a picture of a cheese slicer”) It all boils down to how they choose what to minimise (o maximise), which function
  3. 3. Images from Wikipedia Theoretical physicists study often simplified situations, that are in their simplicity already very hard to describe exactly. They do most of their job even before real data are available.
  4. 4. The function that the Theoretical physicist minimise is called and it summarise how all the elements in your theory (in this case the particle attached to the spring) behave. For isolated, not very involved systems, made of few elements, it is possible to write it and minimise it, not only numerically, but alsoanalytically (taking derivatives to find the minimum).
  5. 5. (in close collaboration with the theoretical physicist) Experimental physicists can choose among different options that the theoretical physicists gave them, in order to minimise the distance Between the data and the line.
  6. 6. The particles don’t start to behave weirdly because they went through a recent break-up
  7. 7. Start from the data, and have no theorist to help them. They study very complex situations, where the noise is often not simply white noise.
  8. 8. Real data are messy, but the value of understanding them for businesses is enormous. DATA SCIENTISTS can help you incorporating this knowledge in your business. Minimisation of some quantity/function is still the way to go! Even a complex Neural Network bases his functionality on minimising some quantity. One needs to cleverly pick the function to minimise in such a way that our result will not overfit the data or be too smooth. In both cases we would end up with miserable predictive power. Picking a suitable function to minimise is an art TRAIN-TEST-PREDICT Another art is to pick the procedure of minimisation (but this is beyond the scope of this talk).

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