自然语言处理 (NLP)资源大全

▍目录

课程

书籍

教程

讲座

框架

论文

博客

学者

数据集

其它

▍课程

CS224d: Deep Learning for Natural Language Processing from Stanford

• Course homepage A complete survey of the field with videos, lecture slides, and sample student projects.

• Course Lectures Video playlist.

• Course notes Probably the best "book" on DL for NLP.

Neural Networks for NLP from Carnegie Mellon University

• Coures homepage

• Course Lectures

• Course code

▍书籍

• Neural Network Methods in Natural Language Processing by Yoav Goldberg and Graeme Hirst

• Deep Learning in Natural Language Processing by Li Deng and Dang Liu

• Natural Language Processing in Action by Hobson Lane, Cole Howard, and Hannes Hapke

▍教程

• Deep Learning for Natural Language Processing (without Magic)

• A Primer on Neural Network Models for Natural Language Processing

• Deep Learning for Natural Language Processing: Theory and Practice (Tutorial)

• TensorFlow Tutorials

• Practical Neural Networks for NLP from EMNLP 2016 using DyNet framework

• Recurrent Neural Networks with Word Embeddings

• LSTM Networks for Sentiment Analysis

• TensorFlow demo using the Large Movie Review Dataset

• LSTMVis: Visual Analysis for Recurrent Neural Networks

▍讲座

• Ali Ghodsi's lecture on word2vec part 1 and part 2

• Richard Socher's talk on sentiment analysis, question answering, and sentence-image embeddings

• Deep Learning, an interactive introduction for NLP-ers

• Deep Natural Language Understanding

• Deep Learning Summer School, Montreal 2016 Includes state-of-art language modeling.

▍框架

• Keras - The Python Deep Learning library Emphasis on user friendliness, modularity, easy extensibility, and Pythonic.

• TensorFlow - A cross-platform, general purpose Machine Intelligence library with Python and C++ API.

• Genism: Topic modeling for humans - A Python package that includes word2vec and doc2vec implementations.

• DyNet - The Dynamic Neural Network Toolkit "work well with networks that have dynamic structures that change for every training instance".

• Google’s original word2vec implementation

• Deeplearning4j’s NLP framework - Java implementation.

• deepnl - A Python library for NLP based on Deep Learning neural network architecture.

▍论文

• Deep or shallow, NLP is breaking out - General overview of how Deep Learning is impacting NLP.

• Natural Language Processing from Research at Google - Not all Deep Learning (but mostly).

• Distributed Representations of Words and Phrases and their Compositionality - The original word2vec paper.

• word2vec Parameter Learning Explained

• Distributed Representations of Sentences and Documents

• Context Dependent Recurrent Neural Network Language Model

• Translation Modeling with Bidirectional Recurrent Neural Networks

• Contextual LSTM (CLSTM) models for Large scale NLP tasks

• LSTM Neural Networks for Language Modeling

• Exploring the Limits of Language Modeling

• Conversational Contextual Cues - Models context and participants in conversations.

• Sequence to sequence learning with neural networks

• Efficient Estimation of Word Representations in Vector Space

• Learning Character-level Representations for Part-of-Speech Tagging

• Representation Learning for Text-level Discourse Parsing

• Fast and Robust Neural Network Joint Models for Statistical Machine Translation

• Parsing With Compositional Vector Grammars

• Smart Reply: Automated Response Suggestion for Email

• Neural Architectures for Named Entity Recognition - State-of-the-art performance in NER with bidirectional LSTM with a sequential conditional random layer and transition-based parsing with stack LSTMs.

• GloVe: Global Vectors for Word Representation - A "count-based"/co-occurrence model to learn word embeddings.

• Grammar as a Foreign Language - State-of-the-art syntactic constituency parsing using generic sequence-to-sequence approach.

• Skip-Thought Vectors - "unsupervised learning of a generic, distributed sentence encoder"（Paper&Code）

▍博客

• the morning paper: The amazing power of word vectors - Overview of word vectors.

• Deep Learning, NLP, and Representations

• The Unreasonable Effectiveness of Recurrent Neural Networks

• Machine Learning for Emoji Trends

• Teaching Robots to Feel: Emoji & Deep Learning

• Computational Linguistics and Deep Learning - Opinion piece on how Deep Learning fits into the broader picture of text processing.

▍学者

• Christopher Manning

• Ali Ghodsi

• Richard Socher

• Yoshua Bengio

▍数据集

Dataset from "One Billion Word Language Modeling Benchmark" - Almost 1B words, already pre-processed text.

▍其它

word2vec analogy demo

Github：https://github.com/brianspiering/awesome-dl4nlp

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