Processing of Natural language, by computers.

Deep learning for NLP Oxford lectures

Techniques

NLP with python

Deep learning

Convolutional neural network, Transfer learning (for learning embeddings), Recurrent neural network (Long short-term memory)

Hybrid character-word NNs: http://arxiv.org/pdf/1604.00788v1.pdf

Latent semantic indexing

Parsing

Google SintaxNet (includes Parsey MacParseface) code. See Grammar

https://demos.explosion.ai/displacy/?text=I%20like%20some%20good%20almonds&model=en&cpu=1&cph=0

http://wiki.opencog.org/w/RelEx_Dependency_Relationship_Extractor

Features for NLP

Word vectors: see Processing our own Data - Deep Learning with Neural Networks and TensorFlow part 5

Language models

Natural language understanding

Visual question/answering system

http://foldr.moe/wordpet/

Software for NLP

Natural Language Toolkit (python) It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries

http://textprocessing.org/tag/information-extraction-in-python

http://www.nltk.org/book/ch07.html