How to build an Azure ML Pipeline - AI42 - S02 Ep. 10

With machine learning becoming more and more an engineering problem the need to track, work together and easily deploy ML experiments with integrated CI/CD tooling is becoming more relevant than ever.

In this session we take a deep-dive into the DevOps process that comes with Azure Machine Learning service, a cloud service that you can use to track as you build, train, deploy and manage models. We zoom into how the data science process can be made traceable and deploy the model with Azure DevOps to a Kubernetes cluster.

At the end of this session you have a good grasp of the technological building blocks of Azure machine learning services and can bring a machine learning project safely into production.

AI AI42 Azure csharplive machine learning

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Ai Fortytwo

AI42 (AI is the answer to all your questions) is an organization that consists of a strong team of two AI MVPs (Microsoft Most Valuable Professional). Together we provide a valuable series of lectures to people who would like to start their career in the field of Data Science and Artificial Intelligence (AI).Our concept is to involve professionals in the field to contribute as speakers at our events, some of our approved speakers are employees of Microsoft. We provide topics which finally allows our students to get a deep, hands-on knowledge in mathematics, statistics, probability, data science and machine learning pipelines. With the help of these lectures our students learn the background required to build a Data Scientist career. The availability and responsibility of the tools and services we discuss during the sessions make our students build trust towards AI.Our streams are going to be available at different platforms: YouTube, Twitch, Facebook, and Twitter.YouTube: https://www.youtube.com/channel/UCYSVVM0ASUGDTeontl4pbxA/Twitch: https://www.twitch.tv/ai42Facebook: https://www.facebook.com/ai.fortytwoTwitter: https://twitter.com/aifortytwo