Meetup #5

High Stakes ML: Active Failures, Latent Factors

Machine Learning Systems play a huge role in several businesses from the Banking industry to recommender systems in entertainment applications until health domains. The era of "A Data Scientist with a Script in a single machine" is officially over in high stakes ML.  We're entering an era of Machine Learning Operations (MLOps) where those critical applications that impact society and businesses need to be aware of aspects like active failures and latent conditions. This talk will discuss risk assessment in ML Systems from the perspective of reliability, safety, and especially causal aspects that can lead to the rise of silent risks in said systems.

In this episode

Flavio  Clesio

Flavio Clesio

Machine Learning Engineer, MyHammer AG

Flavio Clesio is a Machine Learning Engineer (NLP, CV, Marketplace RecSys) and at the moment works at MyHammer AG, where he helps build Core Machine Learning applications to exploit revenue opportunities and automation in decision making. Prior to MyHammer, Flavio was a Data Intelligence lead in the mobile industry, and business intelligence analyst in financial markets, specifically in Non-Performing Loans. He holds a master’s degree in computational intelligence applied in financial markets (exotic credit derivatives).



Demetrios Brinkmann

Demetrios Brinkmann


Demetrios is one of the main organizers of the MLOps community and currently resides in a small town outside Frankfurt, Germany. He is an avid traveller who taught English as a second language to see the world and learn about new cultures. Demetrios fell into the Machine Learning Operations world, and since, has interviewed the leading names around MLOps, Data Science, and ML. Since diving into the nitty-gritty of Machine Learning Operations he felt a strong calling to explore the ethical issues surrounding ML. When he is not conducting interviews you can find him making stone stacking with his daughter in the woods or playing the ukulele by the campfire.