Personalizing content is a complex, dynamic problem where labor-intensive machine learning workflows and costly A/B testing fail to catch up to the nuances of user’s behavior. How do the pros, like XBox One, approach this? In this session we’ll show how businesses can use the new Cognitive Services Personalizer to improve business outcomes and user experience by letting it learn directly from user’s behavior. Personalizer (public preview) makes applied enterprise use of reinforcement learning. It enables full learning loop that runs at digital speed and learns from a simple reward score that optimizes towards your business’s goals. In this session we’ll show you how Personalizer works with your content and data, how it autonomously learns to make optimal decisions, how you can add it to your app with two lines of code, and how to understand what’s under the hood. We’ll share results Personalizer achieved on the Xbox One home page and practices you can use to apply it in your applications today.
In just 60 minutes, this session will demonstrate an end to end data pipeline supplemented by AI to achieve insights real-time. Using components like Azure Functions, Event Hubs, Databricks, Cognitive Services, and Power BI I'll be putting together a pipeline that takes our #msBuild social stream and analyses it realtime. Join me as I show how quickly these sorts of systems can be put together for awesome insight.
Azure operates one of the largest public big data cluster services on the planet. Every day thousands of customers build and operate mission-critical big data analytics, business intelligence (BI), and machine learning (ML) solutions using Azure HDInsight. Come explore architectural best practices, recommended patterns, and tips and tricks for building successful production systems using Apache Spark, Hive, Kafka, and HBase. We will also showcase customer examples and reference architectures.
Today's growing security market has created a big opportunity for developers to build solutions that can dramatically simplify security integration, management, automation, and reporting. Join this session to learn how to create security applications and solutions using our APIs, platform, and open source communities. Our tools help reduce development time and effort to integrate Microsoft and partner solutions. We’ve also invited the winner of the Microsoft Graph Security Hackathon to demonstrated how they used these tools to build their winning app.
Python is a powerful stack running many websites that you know and love, but it can be difficult to get your development environment running smoothly, especially when using technologies like Docker. In this session, we’ll show you how to set up the ultimate containerized Python development environment in Visual Studio Code, deploy your application to Azure with a few clicks, and use Azure DevOps to automate your deployments. Along the way, we’ll cover popular technologies used with Python web applications such as Django, Docker, PostgreSQL, and more!
Millions of user accounts were stolen from a big ride-sharing company recently—all because a developer leaked an important credential on GitHub! Even the best of us make mistakes sometimes. Learn best practices for building applications on Azure, with a focus on secrets management. We will walk in the shoes of a developer and illustrate the tools available to reduce costly mistakes at each stage of a secret’s lifecycle:Discover secrets in source code, config etc using CredScan Eliminate certain types of secretsManage secrets safely, rotate them, and automate their deployment with Azure Key VaultSimplify your code using AppAuthenticationBe prepared for security incidents The design patterns covered in this talk are applicable beyond secrets. You’ll walk away from this session with the checklist of things you can do to reduce security risks to your most critical data.
Data privacy and security are top of mind for almost every enterprise in the world. But creating machine learning in a manner that is secure and privacy-aware presents specific challenges. Learn how to build and deploy secure, protected and scalable machine learning using Azure Machine Learning. Whether you are targeting the cloud or the edge, this session will help you understand how to apply multi-factor authentication, role-based authorization, data encryption, VNETs, and other security and privacy best practices to the machine learning lifecycle.
With Kubernetes quickly becoming the new application deployment infrastructure, traditional enterprise customers are scrambling to understand the new landscape and revamp their enterprise security checklists and tools to secure their applications. In this session, we will examine the container security landscape, walk you through common pitfalls to avoid, and look at capabilities in and around Azure Kubernetes Service that can help.
Learn how Azure Data Explorer service can help you build near real-time and complex analytical solution. We will cover the service overview and demonstrate the querying capabilities on terabytes of data.
If you build SaaS applications that manage multiple customers, this session is for you! Power BI Embedded engineering team will help you weigh the different options across several important evaluation criteria and share design best practices for choosing the tenancy model that best fits your needs.