Machine Learning Short Course
August 5-7, 2019, 9am-5pm
Cornell University, Ithaca, NY
Before June 1st:
Current Cornell faculty, staff, and students: $495.00
All other participants: $550.00
Beginning June 1st:
Current Cornell faculty, staff, and students: $550.00
All other participants: $650.00
Machine learning refers to the use of computational tools and statistical learning to understand large and complex datasets. The goal of most machine learning methods is to identify patterns in the data, simplify data structure by performing data reduction, create models or algorithms that can be used to make highly accurate predictions, or to accurately classify items into categories. This course will provide an introduction to the practice of machine learning, as well as review several common methods. This course focuses heavily on application, so a majority of instruction will be focused on the implementation of these methods.
Researchers from all fields are welcome. This course will provide an introduction to the topics listed below and provide attendees with the knowledge and skills necessary to confidently apply these methods to their own research. No previous background in machine learning is necessary, but we will assume an understanding of multiple linear regression.
Specific topics to be covered include:
- Overview of machine learning methods
- Supervised vs unsupervised learning
- Model evaluation, testing and training, cross validation
- Shrinkage models: lasso, ridge regression and elastic net
- Principal components regression
- Partial least squares
- Logistic regresion
- Linear discriminant analysis
- Classification and regression trees
- Random forests
- Principal components analysis
- Cluster analysis
This course will have a substantial hands-on component using R via RStudio. Participants should have a working knowledge of both R and RStudio (e.g., be comfortable importing and manipulating data, performing simple statistical analyses, and fitting linear regression models). Prior to the Machine Learning short course, participants will be given an opportunity to register for a free introduction to R webinar that will cover the material that participants are expected to be familiar with.
All sessions will be held in a computer lab with PCs that have the most recent versions of R and RStudio installed. Participants are also welcome to bring their own laptop to use during the course, but please make sure to have the most recent version of both R and RStudio already installed. To download and install R, visit https://cran.r-project.org/ and to download and install RStudio, visit https://www.rstudio.com.
There are several options for parking at Cornell University. For more information, please visit: https://fcs.cornell.edu/content/short-term-parking-options
Below are several suggestions for lodging near the Cornell campus. Please be aware that hotel availability in Ithaca can be limited. We recommend making reservations as early as possible.
Best Western University Inn
1020 Ellis Hollow Road, Ithaca NY
The Statler Hotel on the Cornell Campus
130 Statler Drive, Ithaca, NY
Courtyard by Marriott Ithaca Airport/University
29 Thornwood Drive, Ithaca, NY
Hilton Garden Inn Ithaca
130 E Seneca Street, Ithaca, NY
Ithaca Marriot Downtown on the Commons
120 South Aurora Street, Ithaca, NY
If you have any questions about this short-course, please contact us at email@example.com.