Machine-learning expert Mikio Braun moves budding data scientists into the world of big data with this overview of how to do complex data analysis at scale. You'll learn the general concepts behind machine learning, compare small scale and large scale data analysis algorithms, and review the basics of the architectures used in large-scale distributed processing. You'll then explore the use of Spark programming for data flow systems,and the many uses of approximation. Braun also outlines evaluation, feature extraction, and model-selection computing costs in big data analysis. The video closes with a discussion of the relationship between the amount of available data and the complexity of the learning problem.
Mikio Braun is a data scientist researcher, a start-up entrepreneur, and the on-going creator of jblas, the open source library for fast linear algebra in Java. He has a Ph.D. in Computer Science, and works at Zalando.