Track 5: Insightful Frontiers

Azure MLOps

The journey of a machine learning model from inception to production is a long one.

MLOps consists of many different substeps, each with dedicated goals and tools – model training and hyperparameter tuning are just small pieces of the whole cake!

Join our workshop to find out which tools Azure has to offer and how they all play together in symphony.

Learning goal

At the end of the workshop, the participants will know how to use Azure ML and Azure DevOps to deploy MLOps pipelines in the cloud.

Pre-requisites

Basic understanding of ML, Python experience

  • Timo Welti

    Timo’s areas of expertise include data analytics, machine learning, project management, data engineering and data visualisation. He received his PhD in Applied Mathematics from ETH Zürich, where he worked on the foundations of deep learning, and conducted research at the universities of Oxford and Vienna. Timo has been with the team since 2020.

  • Nino Weingart

    Nino holds an M.Sc. and B.Sc. in Computer Science from Swiss Federal Institute of Technology (ETH). Before joining D ONE, Nino worked as a Software and Machine Learning Engineer in Switzerland. Nino also works as a Lecturer on the topic “AI for Manager” and has been with the team since 2021.

  • Spyros Cavadias

    Spyros holds a M.Sc. in Artificial Intelligence from the Katholieke Universiteit Leuven (KU Leuven) and also holds a M.Sc. in Electrical and Computer Engineering from the National Technical University of Athens (NTUA). Before D ONE, Spyros was working on tinyML applications for use on Edge AI devices and he has also worked as a data science expert consulting for the health sector. His area of expertise is machine learning. Spyros has been with the team since 2020.