AI Azure Cognitive Services Clemens Siebler 

Azure Cognitive Services Containers processing time comparison

Introduction Azure offers a rich set of pre-trained AI models called Cognitive Services which can help you solving a large variety of tasks. For example, services like OCR (Optical Character Recognition), form recognition or Speech-to-Text enable you to automate otherwise labor-intensive business processes. Let’s take invoice processing as an example. Historically, this has been performed […]

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Azure Machine Learning Clemens Siebler 

Invoking Azure Machine Learning Pipelines from Azure Data Factory using DataPath

This is a quick post for showing how to call Azure Machine Learning Pipelines from Azure Data Factory. This includes passing data dynamically into the Machine Learning Pipeline using DataPath. Pipeline Creation First, let’s create an AzureML Pipeline that we can use for this example. Please note that this code is syntactically correct, but probably […]

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Automated Machine Learning Architecture
AI Azure Machine Learning Clemens Siebler 

Using Automated Machine Learning for building and deploying Models as APIs

In this post we’ll look into using Azure Automated Machine Learning for deploying Machine Learning Models as APIs into production. As an example, we will be training and deploying a simple text sentiment analysis service, using the IMDB reviews dataset¬†(subsampled to 1000 examples). We will achieve this by building the following architecture: In detail, we […]

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