Is “Introduction to NLP” just “Machine Learning: NLP Edition”?¶
Keynote 2
Day 2: June 11th from 14:00 to 15:00 UTC-04:00 or ET
How to connect: Zoom via Underline
Many of us teach NLP in departments that also teach ML. Some of our students may never take ML, while others may take it before, during, or after NLP. What parts of ML should we teach ourselves? How should we avoid redundancy with the ML class? And at a moment when NLP seems to be focusing on “Transformers everywhere,” what are some broader perspectives on our field that will serve our students well?
Speaker: Jason Eisner¶
Jason Eisner is a professor of Computer Science, with a joint appointment in Cognitive Science, at Johns Hopkins University. He has been involved in NLP education for over two decades and has twice received school-wide awards for excellence in teaching. He now also spends half his time as Director of Research at Microsoft Semantic Machines, where he’s been gratified to see lots of methods from his class in actual use.
Jason has excellent resources for teaching and learning on his web page. For example, check out his courses, teaching statement, his advice for TAs, and his illuminating interview about teaching. We are very excited to have this opportunity to hear about teaching and learning NLP from Jason!!
