caret (Classification And REgression Training) is a package that streamlines the build of machine learning models in R. This workshop will consist of a brief introduction to machine learning and hands-on exercise of building predictive models with caret. Familiarity with R and RStudio Cloud will be useful but not required.
About our speaker:
Trang Le is a postdoctoral fellow with Jason Moore at the Computational Genetics Lab, University of Pennsylvania. She enjoys developing machine learning methods for rigorous analyses of biomedical data, including neuroimage, transcriptomic and genetic. She’s the author and maintainer of three R packages and active contributor of the automated machine learning tool TPOT. She holds a doctorate and a master’s degree in mathematics and two bachelor’s degrees in mathematics and geology. Reproducible research, inclusion and equity.
About our sponsor:
Elsevier fuses evidence-based trusted content, cutting-edge technology and analytics in a range of innovative digital applications for end users in the scientific, academic and medical worlds. Our leading-edge applications, platforms and products are used globally to advance science, aid discovery, improve patient outcomes and to positively impact people’s lives.
- Parking: There is limited street parking and no on-site parking garage. However there are multiple garages in the surrounding area.
- Biking: There is no indoor bicycle storage but there are bike racks outside of the south entrance.
The venue is wheelchair accessible - the main elevators are accessible directly from the lobby. Restrooms are gendered and you are welcome to use whichever you feel most comfortable with. There is a private lactation room available by request and refrigerators in the kitchen off of the meetup space. For accommodations (e.g. visual, verbal, auditory, or other impairments or circumstances) please contact R-Ladies organizers before the event so we can coordinate with our location sponsor.