nlp-quickstart
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神经网络入门介绍 Neural Networks and Deep Learning by Nielsen
LSTM 介绍 Understanding LSTM Networks by Colah
Transformer:
Transformer 介绍 The Illustrated Transformer by Jay Alammar
Transformer 论文 Attention Is All You Need
Transformer Pytorch 实现
Sequence to Sequence Learning with Neural Networks
Attention:
Neural Machine Translation by Jointly Learning to Align and Translate
Effective Approaches to Attention-based Neural Machine Translation
基于 NLTK 库的自然语言处理实践教程 The NLTK Book
基于神经网络的自然语言处理方法的历史演进 A Review of the Neural History of Natural Language Processing by Sebastian Ruder
基于神经网络的自然语言处理常用方法简介 A Primer on Neural Network Models for Natural Language Processing by Yoav Goldberg
基于深度学习的自然语言处理技术最佳实践 Deep Learning for NLP Best Practices
单词级 n-gram 前向神经网络语言模型 A Neural Probabilistic Language Model (Bengio et al., 2001; 2003)
字符级 RNN 语言模型介绍 The Unreasonable Effectiveness of Recurrent Neural Networks
http://ruder.io/word-embeddings-2017/
word2vec paper:
Efficient Estimation of Word Representations in Vector Space
Distributed Representations of Words and Phrases and their Compositionality
word2vec tutorial:
skip-gram by Chris McCormick
negative sample by Chris McCormick
Glove: Global Vectors for Word Representation
A Convolutional Neural Network for Modelling Sentences
Convolutional Neural Networks for Sentence Classification
A Survey of Cross-lingual Word Embedding Models
https://thegradient.pub/nlp-imagenet/
Semi-supervised Sequence Learning
A Unified Architecture for Natural Language Processing: Deep Neural Networks with Multitask Learning(Collobert and Weston 2008)
中文自然语言处理 by 滴滴人工智能实验室
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