The Practitioners’ Lecture Series, March 28-29, 2019
Introduction to back-propagation and automatic differentiation (AAD) in machine learning and finance
Much honored to be invited to give the titular workshop lecture at Kings College London on 28 and 29 March. See the event page here: https://www.eventbrite.co.uk/e/the-practitioners-lecture-series-introduction-to-back-propagation-and-automatic-adjoint-tickets-58436780985
See a brief, non-technical abstract on QuantMinds page here. The 6-hour workshop is a technical one. We will discuss the mathematics of deep learning and back-propagation, and the application of AAD with implementations in Python/TensorFlow and C++. The presentation slides are found on my GitHub repo (Intro2AADinMachineLearningAndFinance.pdf), together with supplementary material: code, spreadsheets and notebooks in the folder ‘Workshop’: https://github.com/asavine/CompFinance
The event was arranged by Blanka Horvath, author of Deep Learning Volatility, where the matter of quick European option pricing in rough volatility models is resolved with deep learning methods. Thank you, Blanka.
Registration is absolutely free, but seating is limited to 40 people. I am looking forward to meet an audience interested in the most recent additions to computational finance.