Primarily focused on the development of complex distributed systems, R&D activities, but enjoys life beyond programming. Agile & lean practitioner and simply a “great product-oriented” developer. Currently interested in microservices architecture, big data trends and applied machine learning for Java engineers. Founder of Morning@Lohika tech talks in Lviv, an active member of JUG Lviv, JEEConf (http://jeeconf.com) and XP Days Ukraine (http://xpdays.com.ua) program committee member.
Machine learning is overhyped nowadays. There is a strong belief that this area is exclusively for data scientists with a deep mathematical background that leverage Python (scikit-learn, Theano, Tensorflow, etc.) or R ecosystem and use specific tools like Matlab, Octave or similar. Of course, there is a big grain of truth in this statement, but we, Java engineers, also can take the best of machine learning universe from applied perspective by using our native language and familiar frameworks like Apache Spark. During this introductory talk, you will get acquainted with the simplest machine learning tasks and algorithms, like regression, classification, clustering, widen your outlook and use Apache Spark MLlib to distinguish pop music from heavy metal and simply have fun.