Damiano Brigo, chair of mathematical finance at Imperial College London, shares his thoughts on the lost causes, the present role and the future prospects of quantitative finance.

Damiano Brigo – 22/01/18

In this podcast excerpt, Ritwik Gupta and Carson Sestili describe deep learning and how it differs from machine learning.  “As you compose more and more non-linear functions together, you can represent a much wider function space than you could with just one non-linear function. That is why deep learning is different from shallow learning. Shallow learning doesn’t compose multiple things together. Deep learning does.”

Deep Learning in Depth: Deep Learning versus Machine Learning

Patrick Zoro welcomes a machine learning expert and explore the finance applications. Hariom Tatsat currently works as a Vice President in the Quantitative Analytics division of an investment bank in New York. Hariom has extensive experience as a Quant in the areas of predictive modelling, and financial instrument pricing in several global investment banks and financial organizations.

Hariom is the co-author of the book "Blueprints for Machine Learning and Data science in Finance".

Patrick Zoro is Professor of Practice and a director of the Master in Financial Engineering Program https://business.lehigh.edu/academics/graduate/masters-programs/ms-financial-engineering

Machine Learning and Data Science in Finance

Created by Professor Patrick Zoro The podcast aims to capture the latest trends in Data analytics, Asset Management, Blockchain, Risk Management.

Patrick Zoro is also the program manager of the Master of Financial Engineering program at Lehigh University

https://cbe.lehigh.edu/academics/graduate/master-analytical-finance

Machine Learning and Data Science in Finance

The Quant / Financial Engineering Podcast

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