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GloVe: Global Vectors for Word Representation Jeffrey Pennington, Â Richard Socher, Â Christopher D. Manning GloVe is an unsupervised learning algorithm for obtaining vector representations for words. Training is performed on aggregated global word-word co-occurrence statistics from a corpus, and the resulting representations showcase interesting linear substructures of the word vector space. Down
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This copy is for your personal, non-commercial use only. Distribution and use of this material are governed by our Subscriber Agreement and by copyright law. For non-personal use or to order multiple copies, please contact Dow Jones Reprints at 1-800-843-0008 or visit www.djreprints.com. http://jp.wsj.com/article/SB10468926462754674708104581082773456994848.html
Machine learning made in a minute The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building production-grade computer vision, computer audition, signal processing and statistics applications even for commercial use. A comprehensive set of sample applications provide a fast start
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Introduction Approximately 25 years of experience Passionate about data privacy and censorship resistance Lead a team of ~30 engineers from hiring to delivering the product to the first customer. Worked in following projects / companies Ethereum Foundation ( worked on Swarm when it was part of Ethereum geth code) Swarm Foundation Prysmatic Labs (worked on PoS Merge) Shardeum Foundation (worked on
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