Amazon Echo, Amazon Tap and Echo Dot have brought voice interfaces to life for the home. We will discuss ways to integrate your existing software or database into an Alexa Skill, allowing for voice-activated, meaningful interaction with a user. Using this SAAS approach, with Web API hosted on Azure can make this process easy for rapid prototyping. We will build and deploy a skill that you can use immediately with your Alexa enabled device, and discuss the challenges of the publishing journey to get in Alexa's Skill Store.

Ever wondered how Azure provides a scalable environment for thousands of applications? This session takes an intermediate look at Azure Service Fabric. You’ll see how Azure uses established patterns and principles to provide an environment that is massively scalable. You’ll also see how that environment is made available to the public as the Service Fabric platform. The session includes some examples of implementing services in the fabric, the various types of services, and recommendations on how to approach creating and architecting services to support scalability and make the most of Service Fabric.

Many organizations use Slack for internal communication. While Slack's chat services are great, there's also a pretty nice platform for building bots that can interact with people, automate tasks & be helpful, or just interject to keep things lively. People usually have chat open all day long so it makes sense for this to be an enabling platform. As a software developer there are a staggering number of simple things you can build as a chat bot for Slack that will bring joy to people's work lives without burning a month of your spare nights and weekends. I'll show you some of Slack's capabilities and how you can use Azure and ASP.NET Web API to quickly build a decent chat bot for your organization.

Complicated workflows getting you down? Well get ready to liven things up with Logic Apps. Create your workflows by doing LESS work and partaking in more "fun".Logic Apps provide a great way to simplify and implement scalable integrations and workflows in the cloud. Using a visual designer, Logic Apps allow you to implement workflows, connect with APIs and access several cloud tools at the click of a button (or two..). In this session, we will go over how to build Logic Apps, how to integrate APIs into your workflow, how Logic Apps can be a great way to handle data and how to connect your Logic App to an active Web Application (Node.js example will be used). This is an ideal introductory session for those curious on how to get started with Logic Apps and workflows and even those interested in learning about different methods of streaming data! It's time to kick back and relax as Logic Apps livens things up for you

Step into the world of Conversational Bots. Taking over platforms one by one, conversational bots are becoming the newest applications wanted and needed by consumers everyday. If you are wanting to learn how to get into the world of Conversation Bots, this talk is for you. Gabrielle will take you step by step on how to get your proper tools, building a bot, deploying it to the cloud and how to get it up and running on different platforms. This is an ideal session for those who are familiar with Node.js and would like to apply it to something new.

If you are thinking of trying out a NoSQL document database, there are many good options available to Microsoft-oriented developers. In this session, we’ll compare some of the more popular databases, including: DocumentDb, Couchbase, MongoDb, CouchDb, and RavenDb. We’ll look at the strengths and weaknesses of each system. Querying, scaling, usability, speed, deployment, support and flexibility will all be covered. This session will include a discussion about when NoSQL is right for your project and give you an idea of which technology to pursue for your use case.

Microsoft Azure Mobile Apps provides a straightforward way to expose backend data to multiple applications on multiple devices. In this presentation, I will show how to expose cloud data access and other processes via a REST interface and connect to that data from applications running on Windows, Windows Phone, iOS and Android. You will also learn how to secure these services; how to scale these services to meet volatile demand; how to push notifications to client apps; and how to manage Mobile Services from within Visual Studio.

Analyzing big data is a challenge, requiring lots of processing power and storage.

Cloud Computing is an ideal platform to tackle this problem. HD Insight on Microsoft Azure deploys Hadoop and other open source big data tools to the cloud, making it easier to take advantage of the high scalability of this platform.

In this session, you will learn what tools are available in HD Insight and how to use them to store, process, and analyze large amounts of data.

Using an EPOC headset from Emotiv, I have captured 14 channels of EEG (brain waves) while subjects lied and answered truthfully to a series of questions. I fed this labelled dataset into Azure Machine Learning to build a classifier which predicts whether a subject is telling the truth or lying. In this session, I will share my results on this “lie detector” experiment. I will show my machine learning model, data cleaning process, and results, along with discussing the limitations of my approach and next steps/resources. Attendees will gain exposure to the Emotiv EPOC headset and Azure Machine Learning.

Interested in doing machine learning in the cloud? In this demo-heavy talk, I will set the stage with some information on the different types of machine learning (clustering, classification, regression, and anomaly detection) supported by Azure Machine Learning and when to use each. Then, for the majority of the session, I’ll demonstrate using Azure Machine Learning to build a model which predicts survival of individuals on the Titanic (one of the challenges on the Kaggle website). I'll talk through how I analyze the given data and why I choose to drop or modify certain data, so you will see the entire process from data import to data cleaning to building, training, testing, and deploying a model. You’ll leave with practical knowledge on how to get started and build your own predictive models using Azure Machine Learning.