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Jev Fever: Predictive AI Is Superhot Again
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GenAI Owns the Hype, but Predictive AI Is Thriving
  EDITOR’S NOTE: This article is adapted from the...
The Data Disconnect: A Key Challenge for Machine Learning Deployment
  EDITOR’S NOTE: This article is excerpted from The...
A Brief History of Why Machine Learning Projects Stall
  EDITOR’S NOTE: This is the preface to The...
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10 years ago
Wise Practitioner – Text Analytics Interview Series: John Herzer and Pengchu Zhang at Sandia National Laboratories

 In anticipation of their upcoming conference co-presentation, Enhancing search results relevance using Word2Vec Language Models at Text Analytics World Chicago, June 21-22, 2016, we asked Pengchu Zhang, Computer Scientist at Sandia National Laboratories, and John Herzer, Enterprise Search Project Lead at Sandia National Laboratories, a few questions about their work in text analytics. Q: In your work with text analytics, what behavior or outcome do your models predict? A: We use the Word2Vec Neural Network model in our search application to predict word usage in our corpus for a particular context.  Word2Vec consists of two models, the Continuous Bag of

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