自然语言处理 (NLP)资源大全

2017 年 9 月 17 日 机械鸡 NLP
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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