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Embeddings have undoubtedly been one of the most influential research areas in Natural Language Processing (NLP). Encoding information into a low-dimensional ve

Text data is important for many domains, from healthcare to marketing to the digital humanities, but specialized approaches are necessary to create features for

Deep learning methods are achieving state-of-the-art results on challenging machine learning problems such as describing photos and translating text from one la

Write modern natural language processing applications using deep learning algorithms and TensorFlow Key Features Focuses on more efficient natural language proc

Word embeddings are a form of distributional semantics increasingly popular for investigating lexical semantic change. However, typical training algorithms are