Do you work at the Brigham? Still looking for a specific resource?
The Brigham Research Education Program is excited to once again offer “A Crash Course in Machine Learning Methods,” a 3-part course that will be taught virtually by Olga Demler, PhD over the course of three Fridays in November (4, 11, 18).
In this course we will review the Machine Learning methods used in medical research. We will also provide a broad overview of Deep Learning methods.
The goal of this course is to develop an intuition for each method and become familiar with the language used in this area. After introducing the basic concepts, we will offer an optional hands-on tutorial of applying these algorithms in the R programming language.
This course assumes a working knowledge of R and intermediate statistical analysis, including linear and logistic regressions and linear discriminant analysis.
This course is based on recent developments in the field (references will be provided) and the books “The Elements of Statistical Learning” by Friedman, Hastie, Tibshirani (https://web.stanford.edu/~hastie/Papers/ESLII.pdf) and “An introduction to statistical learning, second edition” by James, Witten, Hastie, Tibshirani (https://www.statlearning.com/).
Day 1 | Fri, Nov 4 | 9:00-11:30AM | Machine Learning Methods I
Day 2 | Fri, Nov 11 | 9:00-11:30AM | Machine Learning Methods II
Day 3 | Fri, Nov 18 | 9:00-11:30AM | Machine Learning Methods III
The deadline to register is EOD Tues, Nov 1, 2022.