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PyData Mannheim 🧦 🤯 Elevating Parquet 🚀|🌟 Enhancing Predictive Models 🤖
2024-03-05 · 17:00
DataScience and AI: in person in Mannheim and live on PyData.TV on YouTube Agenda 18:00 Doors open 18:30 Welcome 18:45 Going beyond Parquet's default settings – be surprised what you can get - Uwe Korn (QuantCo) 19:15 Break: Networking with snacks and beverages 20:15 Profiling and Optimising Model Prediction Services -Paolo Rechia (Schwarz IT) 20:45 Lightning Talks 21:00 Networking with snacks and beverages 21:30 End Lightning Talks Join us by contributing a five-minute lightning talk! Fill out this form. How to sign up for on site It's important for us to make this meet up happen in a responsible way. We have limited seats available only. No limits to sign up remotely! How to join remotely Join the live stream on YouTube. This event will be in English. ---- Talk #1 Uwe L. Korn (QuantCo) Going beyond Parquet's default settings – be surprised what you can get Apache Parquet has become the de facto format for storing tabular (DataFrame) data on disk. This is done through universal compression and efficient knowledge of the stored data structure. As part of this talk, we would like to show the core structure of Parquet and the knobs that allow you to get even more of the capabilities of the file format. Uwe Korn is a CTO at the data science company QuantCo. His expertise is in building scalable architectures for machine learning services and the teams & culture around them. Nowadays, he focuses on the data engineering infrastructure that is needed to provide the building blocks to bring machine learning models into production. As part of his work to provide an efficient data interchange, he became a core committer to the Apache Parquet, Apache Arrow and conda-forge projects. Talk #2 Profiling and Optimising Model Prediction Services Paolo Rechia (Schwarz IT) Over the past year, Paolo had the opportunity to address performance issues several times, especially in scenarios involving real-time model predictions. Interestingly, in both instances, he found that the slow down was not due to the model prediction itself, but rather steps that occurred beforehand. He is eager to share the step-by-step investigation process he followed and how he successfully resolved these issues. Paolo is a AI Product Engineer / Data Engineer at Schwarz IT. Paolo has a deep passion for computer programming and is always eager to learn new technologies and ideas. His primary interests lie in algorithms, software engineering, and machine learning. ---- Lightning Talks: 1. Jakob Miksch - Handling Geodata with GDAL/OGR 2. Benedikt Prisett - Prompt Injections 3. Simon Pressler - Paying in Forward: Trust in Communities Acknowledgements Also a big thank you to our sponsors:
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PyData Mannheim 🧦 🤯 Elevating Parquet 🚀|🌟 Enhancing Predictive Models 🤖
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