Validation and Machine Learning — Some Thoughts on Deep Neural Networks

QuantUniversity partnered with PRMIA to do the first QuantUniversity summer school in Machine Learning and AI in Finance. We had more than 1000 participants from more than 20 countries including India, China, Australia, UK, Turkey, South Africa etc. attend the summer school series.

This year, we offered 3 courses in Data Science, Machine Learning, and Model Risk Management:

  1. Just Enough Python for Data Science
  2. Machine Learning and AI for Financial Professionals
  3. Model Risk Management for Machine Learning Models

In addition, we had 10 lectures from eminent quants, innovators, and thinkers on various topics in AI/ML and Fintech related topics.

Lecture 9

In Week 9, we had Dr. Jörg Kienitz from Quarternion, Sri Krishnamurthy from QuantUniversity, and Ben Steiner from BNP Paribus Asset Management to discuss their work on Validation and Machine Learning. Here is a summary of the workshop.


Lecture 1: Dr.Jorg Kientz

In this talk, we outline the use of Machine Learning algorithms and their potential application. We focus on Deep Neural Networks. The aim is to outline different network architectures. Then, we wish to find a way of choosing the architecture that best fits from a model validation perspective. This approach is illustrated with examples.

Lecture 2: Ben Steiner

In this talk, we will discuss the challenges of Deep learning and focus on the key aspects of Model Risk Management for Deep Learning and Alpha Strategies

Listen to the Podcast here

Labs, videos, and demos at

If you want to try out the demos yourselves on the QuAcademy:
Use ‘QUSUMMERSCHOOL’ as Registration Code



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