#143 AI in Finance with Matthew Dixon - Assistant Professor of Applied Math & Author

Summary: <p>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. </p> <p>Quotes: </p> <ul> <li>"Do you want uncertainty as your first class citizen or do you want it more as an afterthought?" </li> <li>"You had to fit models to the data. I realised quickly that was the achilles’ heel for the approach." </li> <li>"It isn't just a guessing game." </li> <li>"In the Bayesian world, it sort of turns everything on its head. It says every parameter in your model is a source of error." </li> <li>"I think interpretability is a must. Not only to appease regulators or non technical finance professionals but rather when something goes wrong." </li> </ul> <p>Thanks to our sponsor</p> <p> <a href="//talentinsights.com.au">Talent Insights</a> </p> <p>Read the full episode summary here: <a href="https://www.datafuturology.com/podcast/2021/2/17/143-ai-in-finance-with-matthew-dixon-assistant-professor-of-applied-math-amp-author">Ep 143</a> </p> <p><strong>Enjoy the show!</strong></p> --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message