Deep Learning Natural Language Processing Practice

In recent years, natural language processing (NLP) based on deep learning methods has gradually become mainstream. This book has 8 chapters in total, which mainly introduces deep learning technology in natural language processing tasks, including the theoretical basis of deep learning, deep learning software framework, language model and word vector, sequence model and gradient disappearance/explosion, application of convolutional neural network in the field of NLP, Seq2Seq model and Attention mechanism, large-scale pre-training model, pre-training language model BERT. It also provides advanced application and development examples of natural language processing technology, and includes some practical projects based on the PyTorch deep learning framework. This book can be used as a textbook for undergraduate and postgraduate students majoring in artificial intelligence, computer science, electronic information engineering, automation, etc., And as a reference for researchers and technicians in natural language processing-related fields.