Who needs ChatGPT? Crafting with Hugging Face & Kedro, Scaling with Ray

🎉 Welcome to the Inaugural Event of PyData Milan! 🚀
We're absolutely thrilled to kick off this amazing journey with all of you data enthusiasts and Python lovers! Let's make this first event a memorable start to many more innovative gatherings. 🌟

Agenda:

• 🚪 18:30 Door Opening: Get in, grab a seat, and feel the vibe!
• 🗣 19:00 Talks Start: The international speakers are up with some cool talks!
• 🍻 Post-Talks Socializing: Let's chat, network, and share ideas right at the venue.
• 🍝 Dinner Time: Hungry for more? Join us as we move out for a dinner together!

Venue: Hosted by Plenitude 🏢 📍 Via Ripamonti 85, Milano.

💡 Who needs ChatGPT? Rock solid AI pipelines with Hugging Face and Kedro
Juan Luis Cano Rodríguez, Product Manager for Kedro at QuantumBlack, AI by McKinsey
Artificial Intelligence is all the rage, largely thanks to generative systems like ChatGPT, Midjourney, and the like. These commercial systems are very sophisticated and powerful, but also a bit opaque if you want to learn how they work or adapt them to your needs. What happens inside the 'black box'?
Luckily there are open AI models that you can download comfortably, study without restrictions, and adjust so that they do what you want. This requires some technical knowledge, but thanks to Hugging Face's models and their ecosystem of Python libraries, delving into AI is easier than ever.
You will soon find yourself combining different models, performing different tasks, and creating complex systems. But this complexity can grow very quickly, and soon you'll find yourself with spaghetti code if you are not careful. By using the Kedro catalog and Kedro pipelines, you will be able to organize the code in no time.
In this talk you will learn how you can create complex AI pipelines using Hugging Face transformers, structure them into Kedro projects that cleanly separate code from configuration and data, and deploy them to production so they start delivering value.

Juan Luis (he/him/él) works as Product Manager at QuantumBlack, AI by McKinsey, with a focus on Kedro, an open source data science framework. He has a decade of experience as developer advocate, software engineer, and Python trainer in several industries.
PSF Fellow since 2017, he has made significant contributions to the PyData stack, published several open-source packages, and organized the first seven PyCons in Spain. Currently he is the lead organizer of the PyData Madrid monthly meetups.

🌐 Unlocking scalable ML with Ray on Vertex AI
Ivan Nardini, Google Cloud - Customer Engineer - Smart Analytics, AI and ML
Ray is an open-source framework for scaling AI and Python applications. This hands-on session will guide Python developers and practitioners through the process of harnessing Ray's distributed computing power to scale ML workloads on Vertex AI. Through a practical example, attendees will gain a comprehensive understanding of Ray's capabilities on Vertex AI. And, by the end of this session, participants will have a solid understanding of how to use Ray on Vertex AI to build scalable and performant ML applications.

Ivan Nardini is a customer engineer specialized in Smart Analytics, AI/ML and MLOps at Google Cloud. He is currently collaborating and enabling Data Science developers and practitioners to define and implement AI/ML applications on Vertex AI. His goal is to transform models into assets for companies using Vertex AI. Ivan is passionate about music and he is planning to start drumming again after a long time.

🎉 Can't wait to see you all there! Let's make this first meetup a blast! 💥

📢 Remember to Sign Up! If you can't come, please let us know by canceling your ticket at least one day before the event. This helps us plan better and allows others to attend if they're interested. We look forward to seeing you there!