The 2016 U.S. presidential election will go down as one of the most unexpected occurrences in the country's history. According to the Pew Research Center, 73 percent of all voters said that they were shocked by Donald Trump's victory. Even 60 percent of Trump voters didn't expect their candidate to win. The campaign was certainly an interesting moment in U.S. politics, but data visualization firm Periscopic decided to take this election as an opportunity to learn more about emotional expression. What they found was that President Trump expressed more negative facial emotions during his inaugural address than any other president in nearly 40 years.

Well done in kickstarting Azure Cognitive Services Emotions API. Remember that Emotions API(Project Oxford) is still in "Preview Stage" so not all your images are meant to work (Tried like 10 happiness emotion images and only 1 got processed). Emotion analysis is essential for all industries. We live in a world where emotions are changed instantly so if we analyze and take precautions before bad things happen, we can avoid dramas or even deaths. There used to be emotion reading in police departments.

Temperament has been a key issue in the 2016 presidential election between Hillary Clinton and Donald Trump, and an issue highlighted in the series of three debates that concluded this week. Quantifying "temperament" isn't an easy task, but The Economist used the Microsoft Emotion API to chart the anger, contempt, sadness and surprised expressed in the faces of the candidates during key sequences of the debates, like this from the third debate: Economist Data Journalist Ben Heubl explains how you can analyze emotions in a video file using Python and R. The Emotion API provides scores for eight attributes of emotion as expressed by a face in a still image or video clip. For example, this expression by Donald Trump expresses mostly anger, with a touch of disgust and a soupçon of contempt. Ben provides Python code for passing a video clip into the Emotion API and retriving frame-by-frame emotion scores. He then uses R to analyze and chart the scores: mostly happiness for Clinton; mostly sadness for Trump.

Emotions can be detected remotely using a device that emits wireless signals to help it measure heartbeat and breathing, say researchers at MIT's Computer Science and Artificial Intelligence Laboratory. The new device, named "EQ-Radio," is 87 percent accurate at detecting whether a person is excited, happy, angry or sad--all without on-body sensors or facial-recognition software. "We picture EQ-Radio being used in entertainment, consumer behavior, and healthcare," says the study's lead researcher, Mingmin Zhao. "For example," says Zhao, a graduate student, "smart homes could use information about your emotions to adjust the music or even suggest that you get some fresh air if you've been sad for a few days." Zhao adds that remote emotion monitoring could eventually be used to diagnose or track conditions like depression and anxiety."

Machine Learning is a very hot topic these days. Getting started can be fast and easy. In this video post, I walk through the steps to build a simple Universal Windows Application (UWP) that connects to the Microsoft Cognitive Services and the Emotion API. The Microsoft Cognitive Services are a set of APIs that enable your apps to leverage powerful algorithms using just a few lines of code. They work across lots of various devices and platforms such as iOS, Android, and Windows, keep improving and are easy to set up.

A few months ago, I stumbled upon the API treasure of Microsoft. It was a jaw dropping moment when I saw more than a dozen Artificial Intelligence based APIs. This treasure has a sci-fi name and is known as Project Oxford which was announced in Build 2015 developer conference in San Francisco. As stated on Microsoft's blog - 'Project Oxford helps developer to build more intelligent apps'. This project was developed to provide the developer some complex machine learning that is otherwise not possible for a single developer to build due to time and resource constraints. These APIs will add more fun and the wow factor to an app that wasn't easy before.