Machine Learning Times
Machine Learning Times
Three Ethical Issues Related to Credit Scores
 A reasonable credit score and its accompanying benefits provide...
AI and ML in Health Care: A Brief Review
 Of the many disciplines that are active users of...
Visualizing Decision Trees with Pybaobabdt
 Originally published in Towards Data Science, Dec 14, 2021....
Correspondence Analysis: From Raw Data to Visualizing Relationships
 Isn’t it satisfying to find a tool that makes...

7 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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