Industrial Strength NLP in Python: spaCy for Natural Language Processing
Details
spaCy provides a set of human language technology tools. It can give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize dates, times, and numeric quantities, mark up the structure of sentences in terms of phrases and syntactic dependencies, indicate which noun phrases refer to the same entities, indicate sentiment, extract particular or open-class relations between entity mentions, get the quotes people said, etc.
The point of both spaCy is to provide the foundational building blocks for higher-level and domain-specific text understanding applications.
spaCy is written in Cython, which gives you the combined power of Python and the speed of C
Speaker: Sean Reed
Sean teaches mini-courses and gives talks related to Natural Language Processing, Neural Networks, TensorFlow, and other data science topics because he thinks it is great to figure out how to apply new techniques to solve problems using data. He has a B.S. in Physics from Fordham and an M.A. in Economics from New York University.
You can read more about him via his LinkedIn (https://www.linkedin.com/in/seanreed1/) profile.
For Further Info:
spaCy - Industrial Strength Language Processing in Python ( https://spacy.io/ )