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We are excited to announce our very first event for the Budapest MLOps Meetup!

This event will be organised on the 8th of November and held at McKinsey Digital Budapest (previously IncepTech). Our thanks goes to them for the venue and for the food & beverage supplies!

Schedule:

18:00 - Gates open & arrival

18:30 - A brief opening

18:35 - An introductory talk to the world of MLOps by Jürgen Großmann

19:00 - Short break

19:15 - Scaling AI like a tech native by Nayur Khan

19:35 - Industry Practices and Infrastructures for MLOps by Dennis Muiruri

19:55 - Closing & networking

Our speakers
Jürgen Großmann, Head of Critical Systems Engineering at Fraunhofer FOKUS
Jürgen Großmann (Fraunhofer FOKUS) is an expert in model-based and data-driven software development, model-based testing, as well as security engineering and security testing. He is currently coordinating the European research project IML4E (www.iml4e.org). His research interests include the development of methods, techniques, and tool infrastructures for model-based development, DevOps and MLOps especially in safety critical domains.

Nayur Khan, McKinsey Digital Partner from London
Nayur is a partner with firm’s London office and also part of the QuantumBlack, AI by McKinsey team. He is predominantly focused on helping organizations build capabilities to industrialize and scale artificial intelligence (AI) to improve performance. He assists organizations move away from pilots and experiments with AI to industrialized implementations that run reliably at scale. Nayur frequently represents QuantumBlack at public events and conferences, sharing best practices concerning AI, data, diversity, and software engineering.

Dennis Muiruri, Researcher at University of Helsinki
Dennis Muiruri is a doctoral researcher at the University of Helsinki. His research is focused on MLOps, particularly the deployment of machine learning systems across different computing environments. Previously he has worked in R&D organizations developing software adaptation systems for mobile hardware platforms as well as developing quantitative models in finance.

Machine Learning
Software Architecture
Data Science
Open Source
Software Development

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