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Azure Data Factory and Virtual Networks – Choosing the right integration runtime

Azure Data Factory is Microsoft’s cloud service for creating integration pipelines between different data sources and orchestrating these pipelines to create fully automated integration solutions. Data Factory provides capabilities for simply copying data from one place to another, performing transformations on the data and even employing custom functionality from a wide array of different separate … More Azure Data Factory and Virtual Networks – Choosing the right integration runtime

How to: Using managed identities to access Cosmos DB data via RBAC and disabling authentication via keys

Historically, authenticating against Microsoft’s Cosmos DB service has only been possible in one of two ways: Either by using keys – long passwords that grant you either full read or read-write access to all data in the Cosmos DB account – or by building a custom user management solution that generates short-lived tokens to specific … More How to: Using managed identities to access Cosmos DB data via RBAC and disabling authentication via keys

How to: Easily deploying Azure Machine Learning models to Azure App Service

In this How to I assume you to have some prior knowledge and experience with Azure and Azure Machine Learning. If the latter is completely new you, I whole-heartedly recommend the quite excellent and free “Create no-code predictive models with Azure Machine Learning” learning path by Microsoft to get started! Azure Machine Learning is a … More How to: Easily deploying Azure Machine Learning models to Azure App Service

How to: Automating Automated Machine Learning in Azure Part 2 – Deploying models and preparing training data

This post is the second part in a two-piece series on automating Automated Machine Learning. If you have not yet read the first part, I recommend checking it out first since the solution shown here will be built on top of where we left off last time. Previously I showed you how you can automate … More How to: Automating Automated Machine Learning in Azure Part 2 – Deploying models and preparing training data

How to: Automating Automated Machine Learning in Azure Part 1 – Scheduling AutoML runs

A key concern with machine learning projects is being able to adapt to changes in the real world. This is especially true when the problem you are trying to solve evolves constantly, as any model training is always done using historical data and as such after a while it may no longer represent the problem … More How to: Automating Automated Machine Learning in Azure Part 1 – Scheduling AutoML runs