Data & Model Monitoring for Robustness in Production

Like any software system, pushing ML to production is hardly the beginning of many more challenges. Ensuring that the system will behave as intended, ensuring the robustness of the models in production is key.
On top of regular challenges, ML systems come with their own complexities, mixing DevOps issues with subtle statistical methods. In this talk, Annabelle and Sofiane will give us an overview of the challenges involved in this critical part of the lifecycle and present some practical solutions, followed by a live demo of implementing monitoring.

⏰ Schedule

• 18h30 - 19h00: Welcome & Introduction 👋
• 19h00 - 19h45: Talk 🎙
• 19h45 - 20h00: Q&A Session 🙋‍♀️
• 20h00 - 21h30: Cocktail & Networking 🥂

🎙 About the speakers

Annabelle Blangero is a Senior Manager at Ekimetrics. She started her career as a research neuroscientist. After 8 years of working in universities and laboratories across Europe and the US, she transitioned to Data Science and became proficient in production-ready ML solutions and ethical and responsible AI.

Sofiane Medjkoune is a Senior Data Engineering & Architecture Consultant at Ekimetrics. He's been working with algorithmic processes, including Deep Learning, Optimization Distributed architectures & DevOps. Recently, his focus at Ekimetrics has been on designing and implementing industrialized and scalable data solutions while leading the cloud infrastructure architectures.

🙌 Sponsors

Ekimetrics, founded in 2006, is a European leader in 'data science for business'. The company’s mission is to help customers audit their data opportunities, enrich their analytical capital and deploy actionable solutions to maximise their marketing and operational performance and re-energise business models. With more than 320 data scientists, Ekimetrics is one of the largest independent teams in Europe. Ekimetrics' focus is delivering short-term gains while ensuring the long-term development of its customers' data assets.

nibble is a technology player in the MLOps space helping organisations scale their data-heavy algorithmic initiatives (AI/ML and the likes) with a mix of service and in-house software solutions.

🤩 Audience

This is a meetup for data professionals who want to push forward the productionization of machine learning development within their organizations: data scientists, data engineers, software and devops engineers, data project/product managers...

👋 Contact

For any inquiries, please contact florent@mlops.paris