PyData Amsterdam

🗓️ MARK YOUR CALENDAR! Our upcoming meetups: ✨ 𝐉𝐚𝐧𝐮𝐚𝐫𝐲 21, 2025: Co-organized with Databricks at their Amsterdam office ✨ 𝐅𝐞𝐛𝐫𝐮𝐚𝐫𝐲 20, 2025 Co-organized with IKEA at their Amsterdam office Stay tuned! As soon as the programs are finalized, we’ll share all the details on our Meetup page and LinkedIn channel. Don’t miss out! 🚀

4K Followers! 🎉🌱🫶 3 months ago, our LinkedIn account reached 3K followers, and now we’ve hit 4K! Thank you for growing with us and for helping make our community so great! #PDAmsterdam

Happy Holidays, dear PyData Amsterdam folks! 🎀 Best wishes from all of us on the PyData Amsterdam Committee ❤️. As we wrap up the year, we’re excited to share that we’ve welcomed some new committee members to our team, who will help us continue growing our PyData community. And we’ll have more updates and news coming your way - so see you around 👀👋

⚡️ An energizing meetup at Dexter Energy that’s for sure! First Aletta Heemskerk from Dexter Energy took the stage and enlightened us about her Bayesian approach for forecasting wind power generation, and specially the key part - fitting the wind speed-energy curve 🌬️📈 Key takeaways? - The power of prior information allows for more accurate wind power predictions 🎯 - Bayesian modeling unlocks more transparency compared to parametric approaches as everything is viewed as a distribution 🔮 - Even sparse data can be handled, amongst others through hierarchical modeling 💡 Our second speaker Tatjana Puskarov presented about the methodologies and challenges they faced at Sensorfact when developing data drift detection for their ML system that prevents energy waste 🌱 What to account for when tackling data drift? - Sounds like an open door, but, don’t drift away from all forms of drift; know what kind of drift you want to detect 🧐 - If you detect model drift check the detect and react framework; measure dissimilarity, test it and adapt❗️ - Your underlying data generating process is not stationary ❌ 💙⚡️Big time credits to Dexter Energy for hosting us, the speakers Aletta Heemskerk & Tatjana Puskarov and all other co-organisers Andrei Kurylionak Alexander Backus, Andi Piftor, Lieke Kools, Louis de Bruijn & Alexander Oude Elferink ⚡️🧡 Since this was our last meetup of 2024, on behalf of the whole PyData Amsterdam chapter; thank you all for this pytastic year, have great holidays ahead, and we’d love to see you all again in 2025!! 🫶🎄💫 #pydata #amsterdam #meetup #datascience #AI #machinelearning #forecasting #bayesian #datadrift #networking #knowledgesharing

[Registration Full] 📢 Another November meetup - this is an extra energizing one! ⚡ It's almost exactly one year ago; time for another co-organized meetup with Dexter Energy on November 28 at 18:00 CET at their office in Amsterdam. On this meetup you'll learn more about how to use Bayesian modeling for sparse data coverage from Aletta Heemskerk at Dexter Energy, and additionally different methodologies and challenges of detecting data drift will be discussed by Tatjana Puskarov from Sensorfact. We're excited and hope to see you all there! 🙌 Sign up for the event via meetup 🔗: https://lnkd.in/e-SXuf5n

𝐑𝐞𝐚𝐥𝐥𝐲 𝐞𝐧𝐣𝐨𝐲𝐞𝐝 𝐩𝐫𝐞𝐬𝐞𝐧𝐭𝐢𝐧𝐠 𝐚𝐭 PyData Amsterdam 𝐚 𝐟𝐞𝐰 𝐰𝐞𝐞𝐤𝐬 𝐚𝐠𝐨 📚—𝐬𝐡𝐚𝐫𝐢𝐧𝐠 𝐦𝐲 𝐭𝐚𝐤𝐞 𝐨𝐧 𝐋𝐋𝐌 𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐰𝐢𝐭𝐡 𝐚 𝐜𝐫𝐨𝐰𝐝 𝐨𝐟 𝐚 𝐟𝐞𝐰 𝐡𝐮𝐧𝐝𝐫𝐞𝐝 𝐟𝐞𝐥𝐥𝐨𝐰 𝐝𝐚𝐭𝐚 𝐬𝐜𝐢𝐞𝐧𝐜𝐞 𝐞𝐧𝐭𝐡𝐮𝐬𝐢𝐚𝐬𝐭𝐬! For those just starting with LLM security, here’s some food for thought: 🔒 𝐊𝐞𝐲 𝐋𝐋𝐌 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐓𝐡𝐫𝐞𝐚𝐭𝐬 𝐭𝐨 𝐊𝐞𝐞𝐩 𝐢𝐧 𝐌𝐢𝐧𝐝 Beyond data security and access control, prompt injection attacks pose unique new challenges in AI security. Often overlooked or underestimated, these attacks can bypass guardrails or overwrite instructions, becoming especially relevant when (1) APIs are accessible to unauthenticated users (e.g., customers) or (2) plugins/agents are in use. 🔎 𝐓𝐞𝐬𝐭𝐢𝐧𝐠 𝐟𝐨𝐫 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐖𝐞𝐚𝐤𝐧𝐞𝐬𝐬𝐞𝐬 For starters, manual testing and following recommended principles offer quick easy wins. For more comprehensive assessments, AI red teaming provides a structured way to simulate and address potential threats. PyRIT, a Microsoft open-source Python library, is a great example of how one can automate, simplify, and strengthen red teaming for LLMs. Curious to learn more? 𝐂𝐡𝐞𝐜𝐤 𝐨𝐮𝐭 𝐭𝐡𝐞 𝐟𝐮𝐥𝐥 𝐭𝐚𝐥𝐤 𝐡𝐞𝐫𝐞🎬: https://lnkd.in/eAm7DJcw. Big thanks to Max Knobbout, Joshua Rooijakkers, Eliza Mints and Nghiep Long Huynh for their help and to the PyData organizers for putting together an incredible event!

Thanks to everyone who joined our meetup last night at the Snowflake ❄️ Amsterdam office! We hope you enjoyed the talks, gained valuable insights, made new connections, reunited with old friends, and, of course, enjoyed the food and drinks 🍔 🥐 🍇🍕🥂🍻💡. 𝐤𝐞𝐲 𝐭𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬: Dimitar Nedev and İpek Özlem's talk highlighted Booking.com's journey to create a modern, cloud-based data platform using Snowflake’s capabilities, with a strong focus on user experience and developer productivity. Their approach, which prioritizes open table formats, unified metadata management, and a consistent user interface across tools, reflects a forward-thinking strategy for managing data at scale. 𝐖𝐡𝐲 𝐒𝐧𝐨𝐰𝐟𝐥𝐚𝐤𝐞? ✦ 𝐒𝐜𝐚𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐚𝐧𝐝 𝐄𝐥𝐚𝐬𝐭𝐢𝐜𝐢𝐭𝐲: On-demand compute that keeps costs down and management light. ✦ 𝐄𝐟𝐟𝐨𝐫𝐭𝐥𝐞𝐬𝐬 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭: Snowflake’s SaaS setup lets Booking.com run things with just a six-person team. ✦ 𝐒𝐭𝐨𝐫𝐚𝐠𝐞 𝐅𝐥𝐞𝐱𝐢𝐛𝐢𝐥𝐢𝐭𝐲: Options to store data where they want, like Iceberg tables in their own S3 buckets. ✦ 𝐏𝐨𝐰𝐞𝐫𝐟𝐮𝐥 𝐃𝐚𝐭𝐚 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭: Includes fine-grained access control, data lineage tracking, and stewardship tools to keep data in check. In Peter Lem’s talk, he shared the successful migration of a transaction reconciliation platform from a MySQL-based data warehouse to Snowflake. Driven by the need for better performance, scalability, and cost-efficiency, Actuals adopted a gradual, tenant-by-tenant migration, maintaining existing functionality while leveraging Snowflake's unique features. The result was faster processing, reduced maintenance costs, and higher user satisfaction. This serves as a valuable case study for organizations considering a transition to a modern data warehouse. 𝐊𝐞𝐲 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬: ✦ Pick a data warehouse that truly fits your business needs, focusing on performance, scalability, and cost-efficiency. ✦ A well-thought-out migration strategy is key - keep it gradual, test thoroughly, and prioritize data integrity. ✦ Leveraging new tech and its unique features can be a game-changer, boosting user experience, optimizing processes, and unlocking fresh opportunities for innovation. A huge shout-out to the organizing team from Snowflake and PyData Amsterdam: 🧡 ❄️ Dora K., Maria Nicoletti, Stephanie Andrei, Jason C. Teetz, Elena Drenska, Nikolett Rontó, Astrid Höij, Bas Vlaming, Shunyao Yu ❄️ 💙 See you at our next meetup on November 28! Stay tuned on our LinkedIn and Meetup channels, where we'll announce the program once it’s finalized.🤩

Last month I did a talk at PyData Amsterdam 2024, and the recording is now available! It’s been so nice to hear from attendees who found the session insightful and see posts about it online. Check out my talk about how Adyen utilizes a Python Mono-repository for all data practitioners to be able to move fast and iterate: https://lnkd.in/e5KpAJd4 #PDAmsterdam2024

A couple of weeks ago I had the honour to present at PyData Amsterdam about the use of testcontainers at Nicolab. I had a blast doing it - though it was also a bit more work than anticipated 😅. I'm already thinking about topics to submit for next year. If you missed it, the recordings are finally live. Do also check out the other talks on the channel, there is some real golden content in there! Personally I thoroughly enjoyed the monorepo talk by Adyen's Maico Timmerman. https://lnkd.in/eWtEtGzj Special shoutout to 👋 Vincent Warmerdam for keeping me on track during the preparations ❤️ (his talk was awesome as well).

[Registration Full] 📣 Join our upcoming meetup co-organized with Snowflake ❄️ on November 7 at the Snowflake Amsterdam Office. Get ready to dive into two powerhouse talks on 𝐁𝐞𝐲𝐨𝐧𝐝 𝐭𝐡𝐞 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞: 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐢𝐧𝐠 𝐒𝐜𝐚𝐥𝐚𝐛𝐥𝐞 𝐃𝐚𝐭𝐚 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐂𝐥𝐨𝐮𝐝. First up, the Booking.com Data DevEx crew İpek Özlem & Dimitar Nedev will break down their slick integration of PySpark, Snowflake, and Iceberg, moving massive amounts of data daily while keeping things fast and reliable. In the second talk, Peter Lem will detail the Actuals team's strategic migration from MySQL to Snowflake, addressing technical challenges and showcasing performance improvements in a multi-tenant SaaS environment. Attendees will gain practical lessons and innovative strategies for large-scale data platform development and migration. We have limited spots available, so, be quick to secure your spots 🔗 https://lnkd.in/eHn9qZEw. Looking forward to meeting you in-person soon!