Location

JetBrains Munich. Register for the event here.

About this event

We are proud to present to you our first collaborative event with PyData! The event will be held in-person at JetBrains Munich, where we will be providing drinks and pizza. Register for the event here.

We have exciting talks from two amazing speakers:

1. Practical Text Search or how to beat Elasticsearch (when you have to) by Egor Labintcev, Alyne GmbH

   In this talk, Egor is going to guide you through the process of building a good text search engine when it’s hard to do so. He’ll start by defining what actually makes the text search good (it’s not that trivial), continue with a colourful description of the struggle the speaker went through while building a (relatively) good text search, and culminate by stating the best practices and approaches.

   Speaker

   Egor Labintcev is currently a Senior ML Engineer in the RegTech industry. He builds various text engines ranging from low-resource extreme multi-label classification to ensemble-based text search in complex domains. His current research interest lies in modern retrieval approaches and NLP model interpretability.

2. Fraud Detection with Graph Features and GNN by Nikita Iserson, S&P Global

   Identifying fraudulent behaviors is becoming increasingly more complex as technology advances and fraudsters constantly evolve new ways to exploit people, companies, and institutions. The complexity grows as companies introduce new channels, platforms, and devices for customers to engage with their brand, manage their accounts, and make transactions. Graph neural networks (GNN) are increasingly being used to identify suspicious behavior. GNNs can combine graph structures, such as email accounts, addresses, phone numbers, and purchasing behavior to find meaningful patterns and enhance fraud detection.

   Speaker

   Nikita Iserson is a Lead Machine Learning Engineer at S&P Global with over 10 years of experience in software engineering, data warehouse development, data analytics, and machine learning. He has built demand forecasting, network analysis, recommender systems, digital twins, and much more covering a wide range of industries, including telecom, retail, and banking.