Speaker "Mark Jack" Details Back



Introductory BootCamp: Turning Raw Data into a Useful Working Predictive Model with R.


I am looking forward to summarizing the R bootcamp I co-taught with Frank Hasbani at Anova Analytics in the Atlanta area this summer 2016. The key themes of the eight-weekend bootcamp were: - How to master the repeatable process of predictive analytical modeling from identifying business objectives to building and implementing a predictive analytical data product that creates incremental business value; - How to retrieve data from a variety sources, locations and formats; - How to use data visualization packages to discover useful patterns in your data; - How to develop a deeper knowledge of scientific methods to train, test and measure the performance of your models to identify the best algorithm. Brief illustrations of short code snippets in R that were used in exercises during the bootcamp with the open-source tool RStudio with its packages in data wrangling, machine learning and visualization will round off the discussion.


Experience Data scientist and physicist with several years of experience in computational modeling in particle physics, neuroscience, nanoscience and high-performance computing and 1+ year certified training in machine learning and statistical programming in R. 

Education 2000 Ph.D. Humboldt-Universität zu Berlin, Berlin, Germany. Theoretical Physics. 1997 M.S. Ludwig-Maximilians Universität München, Munich, Germany. Theoretical Physics. 1994 B.S. Ludwig-Maximilians Universität München, Munich, Germany. Mathematics. 1993 B.S. Ludwig-Maximilians Universität München, Munich, Germany.