Combating online payment fraud & putting LLMs in open-source production systems

Join us for the upcoming PyData Amsterdam meetup that we host in collaboration with Adyen.

Schedule

18.00-19.00: Walk in with drinks and food (🍕 /🍺)
19.00-19.45: Fraud or no Fraud: sounds simple, right?
19.45-20:00: short break
20.00-20:45: Building GenAI and ML systems with OSS Metaflow
20.45-21.30: Networking + drinks and bites

[Talk 1]: Fraud or no Fraud: sounds simple, right? by Sophie van den Berg
The surge in online payments has brought a surge in fraudsters looking to exploit the system. To combat this, we're leveraging machine learning (ML) models to identify and block fraudulent transactions. While this may seem like a straightforward supervised learning task, there's a key challenge: how do we confirm if a blocked transaction was truly fraudulent? This talk delves into counterfactual evaluation and other obstacles encountered when building an ML model for fraud detection at Adyen.

[Talk 2]: Building GenAI and ML systems with OSS Metaflow by Hugo Bowne-Anderson
This talk explores a framework for how data scientists can deliver value with Generative AI: How can you embed LLMs and foundation models into your pre-existing software stack? How can you do so using Open Source Python? What changes about the production machine learning stack and what remains the same?

We motivate the concepts through generative AI examples in domains such as text-to-image (Stable Diffusion) and text-to-speech (Whisper) applications. Moreover, we’ll demonstrate how workflow orchestration provides a common scaffolding to ensure that your Generative AI and classical Machine Learning workflows alike are robust and ready to move safely into production systems.

This talk is aimed squarely at (data) scientists and ML engineers who want to focus on the science, data, and modeling, but want to be able to access all their infrastructural, platform, and software needs with ease!