🎉 Kick Off the Year with PyData! First Meetup of 2025! 🐍🚀

New year, new insights, same awesome community! 🎊 Join us for our first PyData meetup of 2025 this February—an evening of great conversations, knowledge-sharing, and networking with fellow data enthusiasts. Whether you're a seasoned pro or just starting your data journey, this is the perfect place to connect, learn, and have fun!

Don't forget to bring good vibes and warmth for a social and informative evening! (+🍕🍔🌯🌮)

---------------------------------------------------------------------------------------------------- "Beyond the ordinary — unconventional approaches to time series classification" by Andrei Lucian

Established techniques such as ANOVA, ARIMA, DBScan, and XGBoost have demonstrated effectiveness in certain contexts. However, I propose exploring unconventional approaches that leverage novel mathematical concepts. This exploration is not necessarily about achieving success, but rather about gaining valuable insights through experimentation.

---------------------------------------------------------------------------------------------------- "Building better chatbots with Knowledge Graphs" by David Lapsanschi

Chatbots powered by Retrieval-Augmented Generation (RAG) are great at pulling information from vast datasets, but they often stumble when it comes to understanding the bigger picture. They miss the subtle connections between ideas, fail to clarify ambiguous queries, and sometimes dish out responses that feel... a bit flat.Enter knowledge graphs: a tool for making sense of relationships between entities. Think of them as a web of interconnected concepts that let chatbots "see" how things are related, not just what they are. By integrating RAG with knowledge graphs, we can give chatbots the power to reason, connect dots, and deliver answers that make sense even in complex conversations.In this talk, we’ll explore how these concepts work together to overcome the limits of standalone RAG. We'll explore together when and why knowledge graphs can be a better solution that can unlock smarter, more dynamic chatbots that go beyond surface-level responses.With some real-world examples and practical insights, we'll show you what we learned in the last year of actively building RAG and knowledge graph solutions.

More importantly, we'll go over the mistakes we made and how they helped us better understand the posibilities and limitations of the current technology.

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