In the last 5 years we observe rapidly increasing interest to artificial neural networks. But what are neural networks and how do they differ from conventional algorithms?
What kind of problems we can resolve with neural networks that could not solve with traditional approaches? In this session we will answer those questions explaining neural networks principles. We will explain concepts behind neural networks and give insight of neural networks usage such as self-driving cars, image recognition, automated translation and text analysis. We will walk you through real life application example: recognition of hand written digits using classical MNIST dataset and convolutional neural network. As a framework Microsoft CNTK and Tensorflow will be used in practical part of presentation.
In a multi-tier application, bottlenecks may occur at any of the connection points between two tiers: business logic and data access layers, client and service layers, presentation and storage layers, etc. Large-scale applications benefit of various levels of caching of information for improving performance and increasing scalability. Caching can be configured in memory or on some more permanent form of storage, in different size and in diverse geographic locations. The open source Redis engine, as implemented in Azure, allows for an intuitive configuration of management of all these aspects, and utilisation from a variety of programming languages.
At EF Education, our applications are used by hundred of thousands of students and staff members daily in 150+ locations world-wide. How do we scale to this mass? How do we optimise performance across regions? This session presents design best practices and code examples for implementing the Azure Redis Cache and tuning the performance of ASP.NET MVC applications, optimising cache hit ratio and reducing “miss rate” with smart algorithms processed by Machine Learning, and for automating and monitoring the deployment of the Redis cache across different tiers, persistence layers and replicated nodes.
We've been hearing a lot about chatbots recently. Are they the next new hot thing in tech? Well, yes and no, there is a lot of hype for something available since late 90s, but they are much smarter and (sometimes) "more human" nowadays, thanks to more accessible AI algorithms in speech processing, NLP, computer vision, etc.
In this session we will touch on their history, look at the current technology stack, build a simple, but smart (sort of) bot using one of the bot frameworks. You will learn how to deploy it and make it available to use in different messaging applications (FB Messenger, Skype, Telegram, etc.). You will discover the challenges and opportunities observed by the industry right now. And perhaps you get some ideas how you can take it further and ... maybe develop that one bot, which will make you rich, or at least entertain your friends!
After the initial excitement of .NET Core wore off (Cross platform! Open source!), we realised there were a few things missing. APIs, mostly.
Oh, and compatibility with a lot of your favourite libraries and packages. Fortunately, the .NET Standard is here to fix all of this, adding back APIs, restoring compatibility and even replacing PCLs. This talk is all about the How and the Why, mixed in with a healthy dose of Why Should I Care. We'll even have a little geek out over the technical details. If type forwarding can't restore your excitement levels to fever pitch, I don’t know what will!
Docker has the potential to revolutionize how we build, deliver, support and even design software. But it doesn't have to be a violent revolution. The end goal might be breaking your existing ASP.NET monolith into microservices which run cross-platform on .NET Core, but the first step can be as simple as packaging your whole application as-is into a Docker image and running it as a container.
In this session we'll take an existing ASP.NET MVC application and package it as a Docker container image, which we can run on Windows Server 2016 and Windows 10. We'll see where the packaging process fits in a CI/CD build, and deploy our app on a clustered Docker Swarm running in Azure. That gives us a scalable, reliable platform for our legacy app, and we'll end by exploring where that can take us.