Microsoft Fabric Data Science - Model scoring with PREDICT

An innovative aspect of this function is its ability to enable users to generate batch predictions straight from a Microsoft Fabric notebook, or directly from the designated item page of a specific model. Microsoft Fabric is at present in its preview phase. However, the video provides extensive guidance on how one can apply the PREDICT function, to those skilled in coding or for those who prefer using a guided UI experience for handling batch scoring.

A requirement for engaging with this innovation is a Microsoft Fabric subscription. There also exists a free version available for trial, which meets the intent of opening the learning curve to interested users who can perform scoring tasks with ease using these tools.

• Microsoft Fabric aids in operationalizing machine learning models
• The function, PREDICT, enables batch scoring across any computing platform
• Batch predictions are feasible through a Microsoft Fabric notebook or a model’s item page
• Microsoft Fabric is still in its preview phase
• Application of PREDICT is direct through coding or via a guided UI experience
• Accessing Microsoft Fabric's capabilities requires a subscription or a free trial

A Brief Insight Into Microsoft Fabric’s Role in Data Science

Microsoft Fabric introduces a novel assortment of tools to the realm of Data Science while concerning itself with the efficient implementation of machine learning models. Their newly unveiled function, PREDICT, stands out for its scalability and adaptability to different computing environments, making batch-scoring achievable and straightforward.

It encourages users to instigate batch predictions based on their comfort with either a guided UI experience or a coding approach, ensuring diverse users find ease in its application. The Microsoft Fabric service is at present in its trial phase but promises to revolutionize the handling of machine learning models and batch predictions, once fully operational

Learn about Microsoft Fabric Data Science: Model Scoring Using PREDICT

In this YouTube video, we get an immersive look into Microsoft Fabric's Data Science capabilities, centering particularly around the cutting-edge function, PREDICT. Microsoft Fabric enables the operationalization of machine learning models with PREDICT, supporting batch scoring across compute engines, and generating batch predictions via the Microsoft Fabric notebook or a specific model's item page.

PREDICT is a scalable function within Microsoft Fabric specifically designed for the operationalisation of machine learning models. It adds the capability of executing batch scoring in any compute engine, and allows the generation of batch predictions either directly from a Microsoft Fabric notebook or from a model's item page. Currently, Microsoft Fabric is only in preview.

• It has been emphasized in the video that users can apply PREDICT in two ways no matter their preference for writing code or using a guided user interface experience for batch scoring.
• For one to utilize the function, a subscription to Microsoft Fabric is required, and the user must sign in to the platform.
• Then, by using the experience switcher icon on the left side of the homepage, the user can switch to the Data Science experience.

To gain a broader knowledge and understanding in this topic, one might consider taking up related training courses. Learning Data Science, Machine Learning, and Microsoft technology-based courses can be interesting and beneficial.

More links on about Microsoft Fabric Data Science: Model Scoring Using PREDICT

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Keywords

Microsoft Fabric Data Science, Microsoft Machine Learning PREDICT, operationalize machine learning with Microsoft Fabric, Microsoft Fabric for batch scoring, Microsoft Fabric notebook for predictions