BlogApplication CapyMOA: Efficient Machine Learning for Evolving Data Streams Dr. Heitor Murilo Gomes, 25. February 2026 Real-time data keeps changing – your models should too. CapyMOA brings high-performance stream learning and concept drift handling to Python, bridging MOA efficiency with practical usability....
BlogResearch qubolite: A Toolbox for Working with QUBO Thore Gerlach, 31. January 2024 Quadratic unconstrained binary optimization (QUBO) problems appear in many different domains such as Machine Learning and Data Mining. We present our light-weight and feature-rich Python package qubolite for working with QUBO....
BlogApplication Snippet Library: Supporting efficient coding Hammam Abdelwaha, 22. September 2021 Writing code is an essential part of a data scientist's everyday life. The Snippet Library extension provides support and enables the quick and easy development of data analysis workflows....
BlogApplication Experiment Tracking: Better documentation of ML experiments with MLflow Claudio Martens, 15. September 2021 Even in the experimental phase of Machine Learning, training processes can be structured clearly and comprehensibly. This blog post presents a helpful tool for this purpose....
BlogApplication Ready Steady Go: Machine Learning in practice Katharina Beckh, 13. January 2021 We describe Machine Learning in practice in three steps: the right mindset, an example process with a system and the right choice of tools. This article provides an introduction and references to resources....
