Unleash Your Model's Potential: Step-by-Step Guide to Deploying a Fabric Machine Learning Model on an Azure ML Inference Endpoint

Microsoft Fabric's Data Science workload leverages Synapse ML for training and are ideally suited to enrich data stored in a data lake. This video walks through the steps to export a model from Fabric, Import it into an Azure ML workspace, and deploy it to a real-time inference endpoint

Deploying and Consuming Foundation Models from the Azure Model Catalog

Explore Azure Machine Learning's selection of pre-trained models from leading sources like OpenAI, Microsoft, and Hugging Face. In this video I'll guide you through the process of choosing, deploying a model on Azure's computing services, and accessing it through a REST API.

How to create and install custom Python libraries in Microsoft Fabric

You've probably used %pip install to include open source libraries in your Fabric notebooks, but did you know you can also easily install your own custom Python libraries?

Unlocking Hidden Insights: Azure OpenAI Meets Fabric in Unstructured Data Analysis

Leverage Azure OpenAI in a Fabric Jupyter notebook to summarize user review data, securely store secrets in Azure Key Vault, and handle data in Fabric Lakehouse’s Delta tables.

How to Apply AI-Driven Sentiment Analysis models in a Fabric Data Lake Solution

This video shows you how to use Azure AI sentiment analysis machine learning models within a Fabric Jupyter notebook to add user sentiment features to Data Lake tables.