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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.
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Tuesday, May 17 • 4:20pm - 4:40pm
byte2vec: a flexible embedding model constructed from bytes

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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.

Speakers
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
Markov

Attendees (16)