This session will focus on what the Microsoft modern principles are, and the steps needed to evolve a common on-premise system architecture to something that is more modern. We will discuss the tenants of modern architecture and why they are important. The speaker will also walk through changes that can be made to update a sample application to a more modern style. Cost factors will be discussed, including the manual work needed, testing, and risks of change.
Windows 8.1 offers an enormous leap forward when it comes to security, and when it comes to malware resistance that couldn’t be more true. It was one of the biggest investment areas in Windows 8 and with Windows 8.1 we’ve added yet another layer of capability. In this session we drill into the details of the malware threats that you’re facing and then show you how you can help your organization and users enjoy a malware free experience on Windows.
By definition, an app written on the Universal Windows Platform can run across many Windows device families, but this covers an extremely wide range of different hardware capabilities (especially to memory and CPU). If you want your app to be successful on all devices, you need to pay attention to these variations, and tune your app’s features dynamically. This talk will explain how the system applies memory and CPU resource policy, and provides insights into the underlying rationale and internal mechanisms. We’ll also see how the new API surface gives you the tools to make your app successful in the face of widely varying hardware constraints. Speaker: Andrew Whitechapel.
Bring your laptop to this session! Azure Machine Learning Studio simplifies machine learning experimentation. In this hands-on tutorial, we will go through the end-to-end process of building, evaluating, fine-tuning and deploying a scalable predictive modelling web service using Azure Machine Learning Studio. By the end of the tutorial, attendees will have a deployed predictive modeling UI of their own, similar to one of these: http://demos.datasciencedojo.com/. All attendees will go through the following hands-on exercises:
• Exploring, visualizing and cleaning a dataset • Building and fine-tuning a predictive model • Evaluating and comparing predictive models • Deploying a predictive model as a full managed, scalable web service • Exposing the deployed predictive model as a web UI.