Webinar Description: In today’s rapidly evolving landscape of artificial intelligence, where agentic and generative AI dominate the conversation, it’s easy to overlook the enduring relevance of traditional machine learning. This session aims to shed light on the value of traditional ML techniques and corresponding capabilities within Microsoft Fabric.

We’ll explore how Fabric empowers data professionals to harness the power of data science through its comprehensive suite of tools and features. From preparing data and training machine learning models to leveraging automated machine learning (AutoML) capabilities and scoring models, Microsoft Fabric offers a seamless experience for developing and operating machine learning solutions.

Additionally, we’ll delve into scenarios where Azure Machine Learning remains indispensable. Despite the advancements in Microsoft Fabric, Azure Machine Learning continues to play a crucial role in handling complex machine learning tasks, providing scalability, and offering specialized services that complement Fabric’s capabilities. We’ll discuss how to effectively join both platforms to leverage their strengths and achieve optimal results in your data science projects. The webinar will highlight how Microsoft Fabric can serve as a robust data platform, seamlessly providing data to models managed and operationalized within Azure ML.

Benefits of attending the webinar – As an attendee, you will explore the core data science capabilities within Microsoft Fabric. Additionally, you will gain a clear understanding of the key differences between Azure Machine Learning and Microsoft Fabric’s data science experience, and learn in which scenarios Azure ML remains relevant. This webinar will empower you to leverage both platforms effectively, optimizing their data science workflows and achieving impactful results.

Is there a demo? I show some of the data science capabilities within Fabric (i.e. model training, experiment and model item in Fabric, model scoring, AutoML). Additionally I might want to show how to integrate OneLake as a data store in Azure ML.

Experience level – Level 300 – Technical

Area of Interest – Developer and Consultant

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