[WiSDOM] Learning Word2Vec Embeddings for Hexcluster Generation 

On October 24, 2019, the WiSDOM (Women in Statistics, Data, Optimization, and Machine Learning) Employee Resource Group hosted the second annual Moving The World With Data meetup, welcoming hundreds of members of the Bay Area tech community to learn about some of our toughest, most interesting data science problems.
During her presentation, data scientist Mo Zhou explains how her approach to crafting the perfect hexclusters borrowed concepts from natural language processing (NLP), leveraging Word2Vec to find embeddings that quantify the similarity between hexagons. She then clusters similar hexagons into small groups where Uber activity is dense, and larger groups where things are less busy. Ultimately, the Uber Eats customer gets a delicious burger and the delivery person and restaurant earn money, and the entire process is more efficient than it would be without Mo’s work.
Learn more about this event: eng.uber.com/moving-the-world...

Наука