Learning all of the services that we use with Microsoft Azure can be overwhelming – especially if you're unfamiliar with Azure and/or the cloud in general.
In this session we'll start at the very beginning, introducing Azure and the core concepts that are the foundation of our cloud platform. We'll start with a discussion of what cloud computing is and what Azure can offer you and your team. We'll then take a look at basic services and features, setting up an account and subscription along the way.
We'll then tour the Azure Portal and do a quick overview of the Resources available and what they do from a high level.
This session will go over three Azure Computer options:
* Logic Apps (Configuration)
* Azure Functions (Code)
* Azure Batch (Massively Parallel compute).
This session will start with a business issue, and finish with a solution using all three of the compute options.
You’ve got a website, but how well is it running? You’ve built your application, but do you know how people are using it?
In this session, you will learn what Azure Application Insights is, a free service offered by Microsoft Azure and what you can do with it. Sure, it’s easy to setup Application Insights with some live analytics, but did you know you can set up your own custom dashboards and alerts to monitor the health of your application? That’s not all… you can use Application Insights to also track logging data, track custom events and even track the telemetry of specific users.
In this session you learn how to to use Microsoft Logic apps to build solutions in Azure and how to answer the following questions:
* What is Logic Apps?
* What can I do with Logic Apps?
* What are the limits of Logic Apps?
You will also see how to build a simple app that sends an email notification.
In this session you will learn what Azure Data Factory (ADF) is, some of the common data connectors it uses, and the data storage options such as blob storage, Azure SQL, Azure Data Lake, Hadoop, etc.
You will also learn how to move data from an on-premises server to Azure.
Is “R” worth the time to learn? What tools will enable me to start? What can I do with “R” if I learn it? How much “R” do I have to know before I can use it?
This session will begin to answer these questions. Almost exclusively demo, we will walk through the use of several visualization techniques to understand and shape data for the purpose of applying Machine Learning Models to make predictions.
Focused on “Binary classification” we will use two predictive algorithms: rxFastLinear and a Gradient Boosting Machine to model Florida Traffic accidents. MS Visual Studio is the tool of choice utilizing Microsoft’s R client.