We have Matthew Dixon, Assistant Professor of Applied Math at the Illinois Institute of Technology and author of the textbook, Machine Learning in Finance: From Theory to Practice. He has also written several journal papers on algorithms and models for machine learning, blockchain based technologies with applications in fintech. 

Quotes: 

• "Do you want uncertainty as your first class citizen or do you want it more as an afterthought?" 
• "You had to fit models to the data. I realised quickly that was the achilles’ heel for the approach." 
• "It isn't just a guessing game." 
• "In the Bayesian world, it sort of turns everything on its head. It says every parameter in your model is a source of error." 
• "I think interpretability is a must. Not only to appease regulators or non technical finance professionals but rather when something goes wrong." 

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Read the full episode summary here: Ep 143 

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