Cortana Intelligence Solutions

James Serra gives an introductory walkthrough to Cortana Intelligence Solutions:

Cortana Intelligence Solutions is a new tool just released in public preview that enables users to rapidly discover, easily provision, quickly experiment with, and jumpstart production grade analytical solutions using the Cortana Intelligence Suite (CIS).  It does so using preconfigured solutions, reference architectures and design patterns (I’ll just call all these solutions “patterns” for short).  At the heart of each Cortana Intelligence Solution pattern is one or more ARM Templates which describe the Azure resources to be provisioned in the user’s Azure subscription.  Cortana Intelligence Solution patterns can be complex with multiple ARM templates, interspersed with custom tasks (Web Jobs) and/or manual steps (such as Power BI authorization in Stream Analytics job outputs).

So instead of having to manually go to the Azure web portal and provision many sources, these patterns will do it for you automatically.  Think of a pattern as a way to accelerate the process of building an end-to-end demo on top of CIS.  A deployed solution will provision your subscription with necessary CIS components (i.e. Event Hub, Stream Analytics, HDInsight, Data Factory, Machine Learning, etc.) and build the relationships between them.

James also walks through an entire solution, so check it out.

Related Posts

When Image Classifiers Look At Unknown Objects

Pete Warden explains that image classifiers aren’t magic: As people, we’re used to being able to classify anything we see in the world around us, and we naturally expect machines to have the same ability. Most models are only trained to recognize a very limited set of objects though, such as the 1,000 categories of the […]

Read More

Building Recurrent Neural Networks Using TensorFlow

Ahmet Taspinar walks us through creating a recurrent neural network topology using TensorFlow: As we have also seen in the previous blog posts, our Neural Network consists of a tf.Graph() and a tf.Session(). The tf.Graph() contains all of the computational steps required for the Neural Network, and the tf.Session is used to execute these steps. The computational steps defined in the tf.Graph can be […]

Read More

Categories

September 2016
MTWTFSS
« Aug Oct »
 1234
567891011
12131415161718
19202122232425
2627282930