Introduction to Deep Learning with TensorFlow

John Urbanic is a Parallel Computing Scientist at the Pittsburgh Supercomputing Center. His research interests include parallel and concurrent computing of all sorts. In particular, high performance and extremely scalable technologies. This includes MPI, OpenMP, OpenACC and threading language extensions. Applying these techniques to the core of Big Data analytics engines such as Spark, as well as enabling modern Machine Learning and the rapidly evolving field of Deep Learning. Performance modeling and optimization of all of these as well.