06-03, 11:00–11:40 (Asia/Jerusalem), Hall 2 (PyData)
This presentation will review the strengths and weaknesses of using pre-trained word embeddings, and demonstrate how to incorporate more complex semantic representation schemes such as Semantic Role Labeling, AMR and SDP into your applications.
Since the advent of word2vec, word embeddings have become a go-to method for encapsulating distributional semantics in NLP applications. This presentation will review the strengths and weaknesses of using pre-trained word embeddings, and demonstrate how to incorporate more complex semantic representation schemes such as Semantic Role Labeling, Abstract Meaning Representation and Semantic Dependency Parsing into your applications.
Aaron (Ari) Bornstein is a Cloud + AI professional with a passion for history, engaging with new technologies and computational medicine. As an Open Source Engineer at Microsoft's Cloud Developer Relations team, he collaborates with Israeli Start-Ups and Communities, to solve real world problems with game changing technologies that are then documented, open sourced, and shared with the developers around the world. To learn more, see: http://aka.ms/israelcda