Distributed Machine Learning 101 using Apache Spark from a Browser by Xavier Tordoir/Andy Petrella
While machine learning has been used for decades, accessibility to these methods is undergoing a radical shift, with the rise of simple interfaces and implementations on distributed systems. In practice it means that more players can afford to take advantage of Machine Learning and at larger scales. In this talk we're going to review some introductory Machine Learning concepts, principles and illustrate them with use cases that could scale to large amount of data using Apache Spark as the processing engine. The illustrative examples will be run directly from notebooks to provide a real life experience, from simple analysis towards how advanced machine learning can be simply applied at very large scale.
November 9, 2015