Create applications using Industry 4.0. Discover how artificial intelligence (AI) and machine learning (ML) capabilities can be enhanced using the Internet of things (IoT) and secured using Blockchain, so your latest app can be not just smarter but also more connected and more secure than ever before. This book covers the latest easy-to-use APIs and services from Microsoft, including Azure IoT, Cognitive Services APIs, Blockchain as a Service (BaaS), and Machine Learning Studio. As you work through the book, you'll get hands-on experience building an example solution that uses all of these technologies―an IoT suite for a smart healthcare facility. Hosted on Azure and networked using Azure IoT, the solution includes centralized patient monitoring, using Cognitive Services APIs for face detection, recognition, and tracking.

You may have come across some of the popular buzzwords going around in the field of computer science such as machine learning and artificial intelligence (AI). As the world of computing is progressing, humans are now prone to delegate many of their tasks to machines. Machine learning and AI are making computers perform tasks that human intelligence can do. In this article, I am going to give you a brief introduction to machine learning and then we will take a deep dive into Azure Cognitive Services. I will also introduce you to the list of Cognitive Services APIs that can be used to solve business problems.

What exactly are Cognitive Services and what are they for? Cognitive Services are a set of machine learning algorithms that Microsoft has developed to solve problems in the field of Artificial Intelligence (AI). The goal of Cognitive Services is to democratize AI by packaging it into discrete components that are easy for developers to use in their own apps. Web and Universal Windows Platform developers can consume these algorithms through standard REST calls over the Internet to the Cognitive Services APIs. So why is it worthwhile to provide easy access to AI? Anyone watching tech trends realizes we are in the middle of a period of huge AI breakthroughs right now with computers beating chess champions, go masters and Turing tests.

This was a big year for Microsoft. The HoloLens began shipping to developers, Windows 10 made it through its first year intact (though not without controversy), and the company got into the desktop computer market with a stunning mega-touchscreen. But there were a few key announcements that flew under the radar this year. While they may not have the splash factor of a Surface Studio or HoloLens, these developments have the potential to alter Microsoft and the world for years to come. At its Build developer conference, Microsoft outlined a vision for a conversational computing platform.

This was a big year for Microsoft. The HoloLens began shipping to developers, Windows 10 made it through its first year intact (though not without controversy), and the company got into the desktop computer market with a stunning mega-touchscreen. But there were a few key announcements that flew under the radar this year. While they may not have the splash factor of a Surface Studio or HoloLens, these developments have the potential to alter Microsoft and the world for years to come. Microsoft's new bot tools help build conversation partners At its Build developer conference, Microsoft outlined a vision for a conversational computing platform.

Microsoft Cognitive Services is a set of cloud-based machine-intelligence APIs that you can use to extract structured data from complex sources (unstructured text, images, video and audio), and add "AI" type features to applications. A good example is the "Seeing AI" glasses in the video below: the image descriptions, emotion inference, and text recognition are all driven by Cognitive Services APIs. You can call these APIs from any application, including R. But since every Cognitive Service API is just a standard REST API, we can use the httr package to call the API. Input and output is standard JSON, which we can create and extract using the jsonlite package. And there are already Python SDKs for many of the services, including the Face API.) Shohbit has also published a step-by-step guide to calling Cognitive Services APIs from R, with several examples of using the Text Analytics API.

All you hear these days is how machine learning and artificial intelligence are the next big things. Your fellow executives, managers, vice presidents and directors are all talking about the need to think about an AI strategy to build business intelligence and create a competitive advantage. Unless you are among a handful of sophisticated technology companies, machine learning and artificial intelligence are way beyond the level of your core competence. You don't have a neural network and wouldn't know what to do with one even if you did. Your IT department just finished (finally) setting up your cloud platform and migrating all of the old company resources to a fancy new public/private hybrid cloud that the executive team spent three years talking about.

Microsoft (NASDAQ:MSFT) is building out Azure as the first artificial intelligence (AI) supercomputer, the company's CEO, Satya Nadella, said at an event in Dublin. Microsoft's existing Azure tools for machine learning (ML) and cognitive computing will see massive adoption due to the company's foray into making the AI supercomputer. This initiative has the potential to empower Microsoft to challenge even IBM's (NYSE:IBM) AI expertise by posing a significant threat to the latter's cognitive computing platform Watson and business intelligence (BI) platform Cognos. With currently being the number 2 player in the cloud IaaS (Infrastructure-as-a-Service) market following Amazon's (NASDAQ:AMZN) AWS, Microsoft can become one of the leading AI players alongside IBM (or might even surpass IBM). At the same time, the software giant can become the number 1 cloud IaaS player, displacing AWS in a shorter span of time than earlier expected.

All you hear these days is how machine learning and artificial intelligence are the next big things. Your fellow executives, managers, vice presidents and directors are all talking about the need to think about an AI strategy to build business intelligence and create a competitive advantage. Unless you are among a handful of sophisticated technology companies, machine learning and artificial intelligence are way beyond the level of your core competence. You don't have a neural network and wouldn't know what to do with one even if you did. Your IT department just finished (finally) setting up your cloud platform and migrating all of the old company resources to a fancy new public/private hybrid cloud that the executive team spent three years talking about. The new DevOps team is finally in place … and may be obsolete before it even starts work.

At Microsoft's Build conference on Wednesday, CEO Satya Nadella laid out his company's vision for the future of artificial intelligence (AI) and machine learning. Microsoft has already made plain its ambitions to make Cortana and its machine learning-based engine more useful and pervasive. Nadella elaborated on those ambitions during Wednesday's Build keynote, describing Microsoft's concept of "conversational computing" and how it will be integrated in everything from Windows, its Edge browser, Outlook and Skype, to the entire ecosystem of software, hardware and cloud-based SaaS offerings. Nadella sees conversational computing using speech as the next user interface and framework for how all applications are developed and connected. In a callback to the name of the conference, Nadella called on developers to "build" the next wave of applications based on tools and services that Microsoft is rolling out, including 22 Cognitive Services APIs for the Azure-based Cortana Intelligence Suite (previously called the Cortana Analytics Suite) and the new Microsoft Bot Framework.