On this blog, we have been often preaching how Machine Learning has been expanding out of its historic habitat of academics and R&D labs into all kinds of industries by powering smart applications. One of the reflections of this trend can be seen in the number of conferences and events that are bringing together real life practitioners and business leaders that are looking for ways to incorporate Machine Learning in their core activities. This year we are witnessing the addition of Machine Learning Prague to that growing event list as possibly the first conference of its kind in Eastern Europe. We are also proud to announce BigML's active participation at the event that will take place on April 23–24, 2016. In the organizers' words "This is not another academic conference. Our goal is to foster discussion between machine learning practitioners and all people who are interested in applications of modern trends in artificial intelligence. You can look forward to inspiring people, algorithms, data, applications, workshops and a lot of fun during both days as well as at the afterparty."

With ever increasing data, Machine Learning is becoming the only way to get analytics done, making it possible to glean insights from vast amounts of data. But when starting a project, it is easy to ignore a critical fact: the value of data is also time sensitive – it expires! In order to get the highest value from data, Machine Learning needs to be applied in a rapid and repeatable way, so you can go from data to insight quickly. A Machine Learning API makes this possible. In this workshop, Poul Petersen CIO of BigML will give an overview of BigML's Machine Learning API and then show real-world examples of predictive applications that can be built using Python and node.js. Several tools that have been built on top of BigML's API will be demonstrated including a loan risk assessment, real estate arbitrage, and the world's first voice controlled predictive assistant.