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2020
Representation Learning for Natural Language Processing
Deep learning has been shown as a powerful method for a variety of artificial intelligence tasks, including some critical tasks in NLP. However, training a deep neural network is usually a very time-intensive process and requires lots of code to build related models. To alleviate these issues, some deep learning frameworks have been developed and released, which incorporate some existing and necessary arithmetic operators for neural network constructions. And these frameworks exploit hardware
doi:10.1007/978-981-15-5573-2_10
fatcat:qs6uihkvjnfmndbdtr32buqt7y