Survival analysis is used when working with data that may be censored, as often is the case in studies of human subjects with incomplete follow-up. The presence of censoring makes most forms of regression and other standard statistical analyses inappropriate. A body of specialized techniques for analyzing this type of data has been developed, including […]
Prerequisites: Participant should have some familiarity with introductory statistics and be able to load data into and perform basic data manipulations in SAS. In this one-day, six-hour workshop we will discuss the basics of using SAS for statistical inference and modeling. The workshop is held in a computer lab and will alternate between instructor presentations […]
Regular expressions are perfectly suited for people who like puzzles. Regular expressions are a sequence of characters used to define a search pattern. They are commonly used to do “find” and “find and replace” string operations. They are also used to validate strings like phone numbers, passwords, etc. in data entry. Regular expression capabilities can […]
Bio: Lyudmyla Barannyk is an Associate Professor in the Department of Mathematics at the University of Idaho. Barannyk received a masters in Applied Mathematics from the New Jersey Institute of Technology and a PhD in Mathematics Sciences from the New Jersey Institute of Technology and Rutgers the State University of New Jersery. She is currently […]
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This is a two-session workshop on the use of Go for data processing. Go is an open source language developed for general-purpose programming. It is not more difficult to learn and use than a high-level scripting language like Python, but it is strongly typed, statically compiled, and provides native support for concurrency, leading to much […]
In this workshop, we’ll first discuss core machine learning concepts such as: choosing loss functions and evaluation metrics; splitting the data into training, validation, and testing sets; and cross-validation patterns for tuning hyper-parameters. Next, we’ll apply these concepts to train models for identifying isolated letters from speech (https://archive.ics.uci.edu/ml/datasets/isolet). Specifically, we’ll apply the elastic net (a […]
Bio: John Harlim is a Professor in the Department of Mathematics and the Department of Meteorology and Atmospheric Sciences. Harlim received his undergraduate degree in Mathematics from the Universitas Padjadaran (Indonesia), a master’s from the University of Guelph in Applied Mathematics, and a PhD in Applied Mathematics and Scientific Computation from the University of Maryland […]
This is a two-session workshop on the use of Go for data processing. Go is an open source language developed for general-purpose programming. It is not more difficult to learn and use than a high-level scripting language like Python, but it is strongly typed, statically compiled, and provides native support for concurrency, leading to much […]
Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level, Python interface running on top of multiple neural network libraries, including the popular library TensorFlow. In this workshop, participants will learn how to quickly use the Keras interface to perform nonlinear regression and classification […]