More than half a century of research in theoretical computer science has brought us a great wealth of advanced algorithmic techniques. These techniques can be combined in a variety of ways to provide us with sophisticated, often beautifully elegant algorithms. This diversity of methods is truly stimulating and intellectually satisfying. But is it also necessary?
A thoughtful article by one of the leading machine learning researchers on whether we can call “machine learning” “artificial intelligence”. Artificial Intelligence (AI) is the mantra of the current era. The phrase is intoned by technologists, academicians, journalists and venture capitalists alike. As with many phrases that cross over from technical academic fields into general… Read More
The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The complete version of the book including lecture materials is available online for free. http://www.deeplearningbook.org/
A presentation on Deep Learning including a brief history and tutorial. https://www.dropbox.com/s/qonozmne0x4x2r3/deepsurveyICML18final.pptx
Having trouble deciding what statistical test to use for your data? Use this handy flowchart from Penn State to decide. It includes a review of all the statistical techniques provided, as well as a table consisting of inferences, parameters, statistics, types of data, examples, analysis, Minitab commands, and conditions. https://newonlinecourses.science.psu.edu/stat500/node/67/
