Recurrent neural networks (RNNs) are a class of neural networks that can process sequential data, such as text. RNNs have been successfully applied to many natural language processing tasks, including text generation, classification, and translation.
Thursday, April 8 - 4:30pm
Location: Virtual, Classroom
Instructor: Akshay Bareja
Wednesday, April 7 - 4:30pm
Location: Virtual, Classroom
Instructor: Akshay Bareja
Recurrent neural networks (RNNs) are a class of neural networks that can process sequential data, such as text. RNNs have been successfully applied to many natural language processing tasks, including text generation, classification, and translation.
Wednesday, April 7 - 1:00pm
Location: Virtual, Classroom
Instructor: Ricardo Henao
Hosted by Ricardo Henao and Michael Pencina
Monday, April 5 - 11:00am
Location: Virtual, Classroom
Instructor: Michael Pencina
Hosted by David Page, Svati Shah, and Michael Pencina.
Wednesday, March 31 - 12:30pm
Location: Virtual, Classroom
Instructor: Christopher Bail
This seminar will discuss one of the most popular techniques for automatically identifying latent or hidden themes in text: topic models.
Monday, March 29 - 11:00am
Location: Virtual, Classroom
Instructor: Matthew Engelhard
Hosted by Matt Engelhard, Ben Goldstein, and Michael Pencina
Wednesday, March 24 - 4:30pm
Location: Virtual, Classroom
Instructor: Augustus Wendell
This workshop presents an ongoing body of work in computational 3D modeling. The topic revolves around the simulation and rendering of spatial geographic forms, in particular landmasses, landforms and large scale geologic features (mountain ranges).
Tuesday, March 23 - 12:00pm
Location: Virtual, Classroom
Instructor: Sarah Rispin Sedlak
Recommendation systems—such as the algorithms powering Netflix, suggesting jobs to apply for, and curating Facebook feeds—are powerful tools that can help users navigate an overwhelming array of choices. However, these systems can have negative side effects if left unchecked.
Wednesday, March 10 - 12:00pm
Location: Virtual, Classroom
Instructor: Christopher Bail
This seminar will provide an introduction to text analysis. Text-based data abounds on social media platforms, digital archives, and elsewhere, but it poses numerous challenges for modeling because it is highly unstructured. We will discuss basic concepts in text analysis (e.g.
Thursday, March 4 - 12:00pm
Location: Virtual, Classroom
Instructor: Christopher Bail
In this seminar, we will learn how to collect data using Application Programming Interfaces. This lecture will introduce key concepts such as credentialing and rate limiting, and provide an example of how to collect data from Twitter.