Episode from the podcastQuPodcast

Episode 3: Dr.Agus Sudjianto : Machine Learning and Model Risk (With a focus on Neural Networks)

Released Saturday, 1st August 2020
Good episode? Give it some love!
Check out the upcoming speakers at: https://qusummerschool.splashthat.com/

Subscribe to this podcast at www.anchor.fm/qupodcast


On Apple Podcast at https://podcasts.apple.com/us/podcast/qupodcast/id…

Slides and video at: https://academy.qusandbox.com/#/library?tagId=5f06…

A conversation with Quants, Thinkers and Innovators all challenged to innovate in turbulent times!

Join QuantUniversity for a complimentary summer speaker series where you will hear from Quants, innovators, startups and Fintech experts on various topics in Quant Investing, Machine Learning, Optimization, Fintech, AI etc.

Topic: Machine Learning and Model Risk (With a focus on Neural Network Models)

All models are wrong and when they are wrong they create financial or non-financial risks. Understanding, testing and managing model failures are the key focus of model risk management particularly model validation.

For machine learning models, particular attention is made on how to manage model fairness, explainability, robustness and change control. In this presentation, I will focus the discussion on machine learning explainability and robustness. Explainability is critical to evaluate conceptual soundness of models particularly for the applications in highly regulated institutions such as banks. There are many explainability tools available and my focus in this talk is how to develop fundamentally interpretable models.

Neural networks (including Deep Learning), with proper architectural choice, can be made to be highly interpretable models. Since models in production will be subjected to dynamically changing environments, testing and choosing robust models against changes are critical, an aspect that has been neglected in AutoML.

Creators & Guests

We don't know anything about the creators of this episode yet. You can add them yourself so they can be credited for this and other podcasts.

Episode Reviews

This episode hasn't been reviewed yet. You can add a review to show others what you thought.

This podcast, its content, and its artwork are not owned by, affiliated with, or endorsed by Podchaser.
Rate Episode

Share This Episode

Recommendation sent

Join Podchaser to...

  • Rate podcasts and episodes
  • Follow podcasts and creators
  • Create podcast and episode lists
  • & much more

Episode Details

1h 5m 9s
Episode Type

Episode Tags

Do you host or manage this podcast?
Claim and edit this page to your liking.