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Wednesday, October 10, 2018 Peer mentoring, NLP presentation and StarSpace Embedding paper review

The Tech Academy
310 SW 4th Ave Suite 230
Portland, OR 97204, us (map)

Note: We're in Suite 230 (the meetup UI won't let me add it) and the doors lock at 5 so we'll have to let you in. Please try to not be too late.



We'll have a short presentation on deep NLP and review the paper "StarSpace: Embed All The Things!"

The major vendors in cloud-based services are starting to provide machine learning as a service, such as Google Cloud AutoML Natural Language and Azure Language Understanding (LUIS). Jim Tyhurst will give a brief demonstration of IBM Watson Natural Language Classifier service (https://www.ibm.com/watson/services/natural-language-classifier/), which enables you to build a custom classifier with no programming. Just create a new instance and submit training data. When the system has finished training, you can submit a document through a web API. The system responds with JSON, giving a list of some possible categories with a confidence score associated with each category. We will discuss some of the advantages and disadvantages of this service.

StarSpace: Embed All The Things! - describes a general-purpose neural embedding model that can solve a wide variety of problems: labeling tasks such as text classification, ranking tasks such as information retrieval/web search, collaborative filtering-based or content-based recommendation, embedding of multi-relational graphs, and learning word, sentence or document level embeddings. https://arxiv.org/abs/1709.03856