You are viewing content from a past/completed QCon - May 2021


State of ML/AI Union

Seeing a new research paper or news article about a new AI model on daily basis? Well, we all do and most of us don’t have a huge amount of them running in production in parallel. We want to take you on a journey that shows you the tools to bring them into production and keep them operational. Join us while we explore MLOps, Feature Stores, and their appliance.

From this track

Session Machine Learning

Developing and Deploying ML Across Teams with MLOps Automation Tool

Wednesday May 26 / 06:10AM PDT

We developed an MLOps automation tool in order to prevent ML engineers working on different projects from continuously repeating the same devops tasks manually. We standardized the management of cloud resources using infrastructure as code as well as model training and deployment workflows using...

Fabio Grätz, Ph.D.

Senior Machine Intelligence Engineer @Merantix

Thomas Wollmann

VP Engineering @Merantix

Session Machine Learning

Unified MLOps: Feature Stores and Model Deployment

Wednesday May 26 / 07:10AM PDT

If you’ve brought two or more ML models into production, you know the struggle that comes from managing multiple data sets, feature engineering pipelines, and models. This talk will propose a whole new approach to MLOps that allows you to successfully scale your models, without increasing...

Monte Zweben

CEO and co-founder of Splice Machine @splicemachine

Session Machine Learning

MLOps: The Most Important Piece in the Enterprise AI Puzzle

Wednesday May 26 / 08:10AM PDT

Machine Learning Operations (MLOps) is a set of principles and practices that increase the efficiency of machine learning workflows and solutions. In this session, Dr. Francesca Lazzeri will provide an overview of the latest MLOps technologies and principles that data scientists and ML engineers...

Francesca Lazzeri

Principal Data Scientist Manager @Microsoft

Session Machine Learning

Iterating on Models on Operating ML

Wednesday May 26 / 09:10AM PDT

What big challenges do we see nowadays in ML?What do we assume to see in the future?How can you sort all your ML models and operate them?Join the discussion with experts actively working on addressing current challenges in building, maintaining, and operating machine learning models. 

Monte Zweben

CEO and co-founder of Splice Machine @splicemachine

Roland Meertens

Product Manager @annotell


Wednesday May 26 / 06:00AM PDT


Machine LearningArtificial Intelligence


Track Host

Jendrik Jördening

CTO @Nooxit

Jendrik is CTO at Nooxit. He formerly worked at Aurubis and Akka Germany on Data Science and Deep Learning in the field of industry 4.0 and autonomous machines.At the same time he took part in the Udacity Self-Driving Car Nanodegree, participating with a group of other Udacity student in the...

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