If you want to use Azure to execute machine learning experiments, you need to reserve some server space in the cloud. In this video I will show you how to log into Azure, create a machine learning workspace and log into Azure Machine Learning Studio so you can execute machine learning experiments.
Cortana Analytics is a fully managed big data and advanced analytics suite that helps you transform your data into intelligent action. Come to this two-part session to learn how you can do "big data" processing and storage in Cortana Analytics. In the first part, we will provide an overview of the processing and storage services. We will then talk about the patterns and use cases which make up most big data solutions. In the second part, we will go hands-on, showing you how to get started today with writing batch/interactive queries, real-time stream processing, or NoSQL transactions all over the same repository of data. Crunch petabytes of data by scaling out your computation power to any sized cluster. Store any amount of unstructured data in its native format with no limits to file or account size. All of this can be done with no hardware to acquire or maintain and minimal time to setup giving you the value of "big data" within minutes.
Good developers try to make their jobs as easy as possible. We know our application will evolve and will need to scale, so we try to make future changes as simple as possible by layering and decoupling our architecture up front. That's great, but can we do more? Your API should be the most important part of your application, especially if you're deploying to the cloud. By focusing on the API first, you'll reap huge benefits in support and bug fixing, and you'll open your application up to massive scale and new features with minimal effort. With plenty of examples and live demos, this session is a practical guide to writing API-driven applications.