Data Science with Java
A good Data Scientist knows how to do something really well, but a great data scientist can do “something of everything”. From raw data all the way to shining in front of C-level executives, a great data scientist has the skills to architect data systems, build applications, perform modeling and machine learning and wrap up the results in a clear presentation that tells a story. Few programming languages can handle all of those tasks. While languages like R and python have cemented their place in the data science community, Java has yet to grab the data science mindshare it deserves. In this talk we will break down some of the barriers to mastering data science with Java and demonstrate a simple approach to statistical and machine learning algorithms.
Michael Brzustowicz is a Senior Data Scientist at Google and teaches Data Science as an Adjunct Professor at the University of San Francisco. After a PhD in Biophysics from Indiana University, Michael spent his post doctoral years at Stanford University. Jumping ship from academia, he worked at many startups (including his own) and has been pioneering big data techniques all the way. Michael specializes in building distributed data systems and extracting knowledge from massive data. He spends most of his time writing customized, multithreaded code for statistical modeling and machine learning approaches to everyday big data problems.
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