Why R? Webinar 010 - Julia Silge - Understanding Word Embeddings

Financed by the 'Perfect Science' program of the Polish Minister of Science and Higher Education

• stream https://youtu.be/ke03DGvT8uU
• Bio + Abstract: Below!
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• join Why R? Slack http://whyr.pl/slack/
• join Meetup http://tiny.cc/WarsawRUG
• format: one 45 minutes long stream + 10 minutes for Q&A
• comments: ask questions on YouTube live chat

Abstract: Modern natural language processing frameworks (including word2vec, GloVe, fastText, ULMFIT, and more) depend on word embeddings, a way of statistically modeling language where words or phrases are mapped to vectors of real numbers. In this talk, understand word embeddings by investigating how we can generate them using count-based statistics and dimensionality reduction, then learn how to make use of pre-trained embeddings based on enormous datasets. Finally, explore the ethical issues involved in using word embeddings and how they can amplify systemic and historical bias.

Bio: Julia Silge is a data scientist and software engineer at RStudio PBC (https://rstudio.com/) where she works on open source modeling tools. She is both an international keynote speaker and a real-world practitioner focusing on data analysis and machine learning practice, and is the author of Text Mining with R (https://www.tidytextmining.com/) with her coauthor David Robinson. She loves text analysis, making beautiful charts, and communicating about technical topics with diverse audiences.