Tài liệu Thư viện số

Danh mục TaiLieu.VN

Neural network methods for natural language processing

Neural Network Methods for Natural Language Processing" by Yoav Goldberg is a comprehensive guide to using neural networks for natural language processing (NLP). The book covers various topics related to NLP such as language modeling, part-of-speech tagging, syntactic parsing, and sentiment analysis.

The book starts with an introduction to neural networks and their applications in NLP, followed by an overview of the basic concepts of NLP such as language modeling and word embeddings. The author then covers various neural network architectures such as feedforward neural networks, recurrent neural networks, and convolutional neural networks, and their applications in NLP.

The latter part of the book delves into specific NLP tasks and techniques for solving them using neural networks. The author covers techniques for part-of-speech tagging, named entity recognition, syntactic parsing, and sentiment analysis using neural networks.

The book also includes code examples and practical tips for implementing neural network models for NLP tasks using popular frameworks such as TensorFlow and PyTorch.

Overall, "Neural Network Methods for Natural Language Processing" is a great resource for anyone who is interested in learning how to use neural networks for NLP tasks. The book provides a solid foundation in neural networks and their applications in NLP, and covers various techniques for language modeling, part-of-speech tagging, syntactic parsing, and sentiment analysis.

Call no. : 006.3 G618

Từ khóa: Neural language processing, Neural network

16 p ovanketv4 09/05/2023 215 2

Bạn đang xem trang mẫu tài liệu này.
Bình luận