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Updated
Mar 19, 2022 - Python
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spaCy is a free library for advanced Natural Language Processing (NLP) in Python. It’s designed specifically for production use and helps you build applications that process and “understand” large volumes of text. It can be used to build information extraction or natural language understanding systems.
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.
the open-source virtual assistant for Ubuntu based Linux distributions
A full spaCy pipeline and models for scientific/biomedical documents.
Hey guys,
I recently switched jobs, and a bit busy these days, and for some reason the volume of issues/requests has increased slightly over the last few weeks.
I'm looking for someone to help me manage the repo, verify pull requests, answer some issues? All I can offer is your name somewhere in the readme (and a coffee/beer if you're in Singapore !)
If you're interested let me know, it'
skweak: A software toolkit for weak supervision applied to NLP tasks
Full text geoparsing as a Python library
NLP in Python with Deep Learning
YAML files appear to be better suited for storing configuration data than JSON.
-Config file -- Should be converted to a YAML file.
-Config reader -- This should probably be deleted and we can let a library like PyYAML h
SpikeX - SpaCy Pipes for Knowledge Extraction
Information extraction from English and German texts based on predicate logic
Created by Explosion
Latest release 20 days ago
The models and algorithms in https://github.com/boudinfl/pke#implemented-models are similar to Textrank but not sped up by SpaCy, so it might be a good idea to include them in PyTextRank
PS: There are also other non TextRank-esque algorithms to consider when making this assessment: