PyData Rhein-Main - Artificial Intelligence in Python

How to join remotely
Join the Zoom meeting or you can also watch the talks on YouTube.

This event will be in English.

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Talk #1
Boosting Time Series Accuracy: The Power of Ensemble Methods - Robert Haase (Paretos)
This talk explores the practical application of ensemble methods in time series analysis, based on Robert’s extensive experience at Pareto. It covers various ensembling approaches, highlighting their effectiveness in different real-world scenarios. Attendees will gain insights into which methods perform best in practice, supported by behind-the-scenes examples of successful implementations. The session provides valuable strategies for improving predictive accuracy, making it ideal for anyone looking to leverage ensemble techniques in their time series projects.
Robert earned both his Bachelor's and Master's degrees in Physics from the University of Heidelberg, specializing in Condensed Matter Physics and Computational Physics. During his Master's thesis in 2020, he advanced existing NLP Transformer architectures for timeseries applications. This involved Robert working extensively with uncertainty quantifications and normalizing flows. Since the beginning of 2021, he has been employed at Paretos, where the primary focus of his work lies in Timeseries Forecasting, specifically demand forecasting. Robert has a keen interest in combining traditional statistical methods with deep learning techniques.

Talk #2
Unleashing Confidence in SQL Development through Unit Testing - Tobias Lampert (Lotum Media)
As data-driven applications grow, robust SQL development practices are crucial. This talk explores the challenges of maintaining complex SQL models in Data Warehouses and highlights the importance of unit testing in ensuring data quality. Attendees will learn how SQL unit testing validates modeling logic, prevents breaking changes, and supports faster deployment cycles. The session features Lotum’s Python-based SQL unit testing framework for BigQuery, which processes millions of daily events from mobile games. Discover how using small, static mock data simplifies testing and helps identify code errors efficiently.

Tobias Lampert is an experienced technical leader with expertise in Data Science and Data Engineering. With over 20 years of experience, he has designed and implemented data-intensive applications end-to-end, covering everything from data ingestion to deployment. He has developed solutions that generate insights from data using statistical analysis and machine learning. His passion lies in building user-friendly, high-performance, and cost-efficient data platforms.
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Acknowledgements
Also a big thank you to our partners:

• Hessian.AI, for hosting the meetup.
• PIONEERS HUB, for organising.

Contact
If you have any questions or suggestions, please feel free to contact us via:

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