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Event

PyData Hamburg July 24th Meetup

2025-07-24 – 2025-07-24 Meetup Visit website ↗

Activities tracked

2

🗺️ Where: Netlight Office, Kaisergalerie 23-27, 20354 Hamburg ⭐️Agenda⭐️: •⁠ ⁠18:00 - Open Doors •⁠ ⁠18:20 - Short Intro •⁠ ⁠18:30 -19:00 First Talk(Viking Björk Friström) and Questions •⁠ ⁠19:00 - 19:30 Break -Networking & food/snacks •⁠ ⁠19:30 - 20:00 Second Talk(Till Nicke) and Questions •⁠ ⁠20:00 - 20:45 Networking & food/snacks

First Speaker: ✨Viking Björk Friström Linkedin: https://www.linkedin.com/in/vikingbf/ The First topic: Using FastAPI + Pydantic for developing event driven ML architecture using python Building production-ready ML systems is rarely straightforward—especially when predictions must be triggered by real-world events in near real time. In this talk, I’ll walk through how FastAPI and Pydantic can be used to architect an event-driven ML system, where model workflows are orchestrated using message queues and jobs vary in latency and compute requirements. The goal is to show how Python developers can move fast while maintaining control over validation, orchestration, and deployment in complex ML architectures.

Second Speaker: ✨Till Nicke Linkedin: https://www.linkedin.com/in/till-nicke-5a5564193/ The Second topic: Image and data analysis in digital pathology with python. Why and How? Abstract: In this talk we will explore the world of imaging in digital pathology and discover gigapixel images and how to look at them. We will learn how deep learning can help predict cancer recurrence in the case of prostate cancer and how models can help pathologists discover new biomarkers.

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Image and data analysis in digital pathology with python. Why and How?

2025-07-24
talk

Abstract: In this talk we will explore the world of imaging in digital pathology and discover gigapixel images and how to look at them. We will learn how deep learning can help predict cancer recurrence in the case of prostate cancer and how models can help pathologists discover new biomarkers.

Using FastAPI + Pydantic for developing event driven ML architecture using python

2025-07-24
talk

Building production-ready ML systems is rarely straightforward—especially when predictions must be triggered by real-world events in near real time. In this talk, I’ll walk through how FastAPI and Pydantic can be used to architect an event-driven ML system, where model workflows are orchestrated using message queues and jobs vary in latency and compute requirements. The goal is to show how Python developers can move fast while maintaining control over validation, orchestration, and deployment in complex ML architectures.