Deep Learning For NLP - Links
Important links for articles, presentations, videos, repos, etc. that I'm collecting related to NLP + Deep Learning
NLP & Neural Networks/Deep Learning
Word2Vec & Continuous Representation
- The Amazing power of word vectors - The Morning Paper
- A BRIEF HISTORY OF WORD EMBEDDINGS (AND SOME CLARIFICATIONS) - Gavagai
- On word embeddings - Part 1 - Sebastian Ruder
- Word2vec Tutorial - Gensim - RADIM ŘEHŮŘEK
- Bengio et al 2003
- Word2vec explained - Xin Rong
- Glossary of Deep Learning: Word Embedding - Jaron Collis
- (Video) Word Embeddings explained and visualized - Xin Rong
- wevi: word embedding visual inspector
- Word2Vec Tutorial - The Skip-Gram Model - Chris McCormik
- Word2Vec Resources - Chris McCormik
- (github repo) inspect_word2vec - Chris McCormik
- Word2Vec tutorial - Alex Minnaar
- NLP (almost) from scratch - Collobert et al
- (video) The Roadmap towards to Machine Intelligence - Tomas Mikolov
- (tutorial) TensorFlow 07: Word Embeddings (2) – Loading Pre-trained Vectors
- (SO) Using pre trained word embedding vector in TensorFlow
- Semantics with dense vectors
- (SO) Significance of using Negative sampling for w2v
Others
- A Primer on Neural Network Models for Natural Language Processing - Yoav Goldberg
- UNDERSTANDING CONVOLUTIONAL NEURAL NETWORKS FOR NLP - WildML
- IMPLEMENTING A CNN FOR TEXT CLASSIFICATION IN TENSORFLOW - WildML
- (github) NLP Datasets
- Visualizing high dimensional representations
- (github) NeuroNER - Neural networks based NER
- A beginner's guide to understanding Convolutional Networks - Adit Deshpande
- Neural Networks Zoo
- Tensorflow for poets
- Deep learning 101
- A brief history of neural nets and deep learning
- On the origin of deep learning
- comp.ai.neural-nets newsgroup
- Ask Me Anything - Ankit Kumary et al.
- Efficient BackProp - Yann LeCun
- (SO) Comprehensive list of activation functions
- Types of Optimizers
- Autoencoders in Keras
- Exploring the limits of Language Modeling
- A primer on Neural Network Models for Natural Language Processing - Yuav Goldberg
Possible good resources on ML/DL
- Alex Minnaar Machine Learning
- Chris McCormik ML
- Ian Goodfellow et al. Deep Learning
- Machine learning mastery blogs
- Neural networks and deep learning
- (github) Machine learning for software engineers
- (github) Perceptron - a neural network building tool for learning/experimenting
- (github) Awesome Machine Learning - A curated list of awesome Machine Learning frameworks, libraries and software.
- (github) The most cited deep learning papers
- (github) ML From Scratch - bare bones python implementation of ML algorithms
- (github) CS AI courses
- Fast AI - Practical Deep learning for coders
- AI Playbook useful links - Andreesen Horowitz
- A neural sequence modeling
- Awesome NLPhttps://github.com/keon/awesome-nlp
Q&A:
- Teaching Machines to comprehend - DeepMind
- (github) rc-data - DeepMind
- Question Answer dataset
- Stanford Question Answering dataset - Kaggle
- Stanford Question Answer dataset
- The Allen AI Science Challenge - Kaggle
- Question Answering using Deep learning - Stanford student report
- Deep Learning for answer sentence selection
- Microsoft WikiQA: A Challenge Dataset for Open-Domain Question Answering
- Intro to deep learning for q&a
- A Knowledge-grounded neural conversational model
- Improved Representation Learning for Question Answer Matching
- End to End Long Short Term Memory Networks for Non-Factoid Question Answering
- End-to-End Non-Factoid Question Answering with an Interactive Visualization of Neural Attention Weights
RNN:
- A critical review of Recurrent Neural Networks for Sequence Learning - Lipton et al.
- Visualizing and Understanding Recurrent Networks - Karpathy et al.
- Understanding LSTMs - Chirstopher Olah
- A beginner's guide to Recurrent Networks and LSTMs - DeepLearning4j
- The Unreasonable Effectiveness of RNNs - Andrej Karpathy
- Recurrent Neural Network based Language Model - Mikolov et al.
- Supervised Sequence Learning with Recurrent Neural Networks - Alex Graves, University of Toronto
- Recursive Deep Learning for Natural Language Processing and Computer Vision - Richard Socher
- Long Short Term Memory in Recurrent Neural Networks - Felix Gers
- A survey on the application of recurrent neural networks to statistical language modeling - De Mulder et al.