This event has ended. View the official site or create your own event → Check it out
This event has ended. Create your own
Data By the Bay is the first Data Grid conference matrix with 6 vertical application areas  spanned by multiple horizontal data pipelines, platforms, and algorithms.  We are unifying data science and data engineering, showing what really works to run businesses at scale.
View analytic
Tuesday, May 17 • 4:20pm - 4:40pm
byte2vec: a flexible embedding model constructed from bytes

Sign up or log in to save this to your schedule and see who's attending!

In today's fragmented, globalized world, supporting multiple languages in NLU and NLP applications is more important than ever. The inherent language dependence in classical Machine Learning and rule-based NLP systems has traditionally been a barrier to scaling said systems to new languages. This dependence typically manifests itself in feature extraction, as well as in pre-processing steps. In this talk, we present byte2vec as an extension to the well-known word2vec embedding model to facilitate dealing with multiple languages and unknown words. We explore its efficacy in a multilingual setting for tasks such as Twitter Sentiment Analysis and ABSA. Byte2vec is an embedding model that is constructed directly from the rawest forms of input: bytes, and is: i. truly language-independent; ii. particularly apt for synthetic languages through the use of morphological information; iii. intrinsically able to deal with unknown words; and iv. directly pluggable into state-of-the-art NN architectures. Pre-trained embeddings generated with byte2vec can be fed into state-of-the-art models; byte2vec can also be directly integrated and fine-tuned as a general-purpose feature extractor, similar to VGGNet's current role for computer vision.

avatar for Parsa Ghaffari

Parsa Ghaffari

CEO & Founder, AYLIEN
Parsa Ghaffari is an engineer and entrepreneur working in the field of Artificial Intelligence and Machine Learning. He currently runs AYLIEN, a leading NLP API provider focused on building and offering easy to use technologies for analyzing and understanding textual content at scale.

Tuesday May 17, 2016 4:20pm - 4:40pm

Attendees (16)