Displaying 1 to 13 from 13 results

NLP-Models-Tensorflow - Gathers machine learning and Tensorflow deep learning models for NLP problems, 1

  •    Jupyter

NLP-Models-Tensorflow, Gathers machine learning and tensorflow deep learning models for NLP problems, code simplify inside Jupyter Notebooks 100%. I will attached github repositories for models that I not implemented from scratch, basically I copy, paste and fix those code for deprecated issues.

kagome - Self-contained Japanese Morphological Analyzer written in pure Go

  •    Go

Kagome is an open source Japanese morphological analyzer written in pure golang. The MeCab-IPADIC and UniDic (unidic-mecab) dictionary/statiscal models are packaged in Kagome binary. Kagome has segmentation mode for search such as Kuromoji.

nlpnet - A neural network architecture for NLP tasks, inspired in the SENNA system

  •    Python

Gitter is chat room for developers. nlpnet is a Python library for Natural Language Processing tasks based on neural networks. Currently, it performs part-of-speech tagging, semantic role labeling and dependency parsing. Most of the architecture is language independent, but some functions were specially tailored for working with Portuguese. This system was inspired by SENNA.

engtagger - English Part-of-Speech Tagger Library; a Ruby port of Lingua::EN::Tagger

  •    Ruby

A Ruby port of Perl Lingua::EN::Tagger, a probability based, corpus-trained tagger that assigns POS tags to English text based on a lookup dictionary and a set of probability values. The tagger assigns appropriate tags based on conditional probabilities--it examines the preceding tag to determine the appropriate tag for the current word. Unknown words are classified according to word morphology or can be set to be treated as nouns or other parts of speech. The tagger also extracts as many nouns and noun phrases as it can, using a set of regular expressions. The set of POS tags used here is a modified version of the Penn Treebank tagset. Tags with non-letter characters have been redefined to work better in our data structures. Also, the "Determiner" tag (DET) has been changed from 'DT', in order to avoid confusion with the HTML tag, <DT>.

SudachiPy - Python version of Sudachi, a Japanese morphological analyzer.

  •    Python

SudachiPy is a Python version of Sudachi, a Japanese morphological analyzer. Sudachi & SudachiPy are developed in WAP Tokushima Laboratory of AI and NLP, an institute under Works Applications that focuses on Natural Language Processing (NLP).


  •    R

First install Python version 2.5+ (not version 3) and the pattern package (https://github.com/clips/pattern). Mark that the pattern package is released under the BSD license. Make sure your when you run the R version (64/32 bit) it is the same as the Python version you installed (64/32 bit). Advise: don't use RStudio, but just plain R when executing the code. Mark that the pattern.nlp package is released under the AGPL-3 license.

RDRPOSTagger - R package for Ripple Down Rules-based Part-Of-Speech Tagging (RDRPOS)

  •    R

R package to perform Parts of Speech tagging and morphological tagging based on the Ripple Down Rules-based Part-Of-Speech Tagger (RDRPOS) available at https://github.com/datquocnguyen/RDRPOSTagger. RDRPOSTagger supports pre-trained POS tagging models for 45 languages. The R package allows you to perform 3 types of tagging.

udpipe - R package for Tokenization, Parts of Speech Tagging, Lemmatization and Dependency Parsing Based on the UDPipe Natural Language Processing Toolkit

  •    C++

This repository contains an R package which is an Rcpp wrapper around the UDPipe C++ library (http://ufal.mff.cuni.cz/udpipe, https://github.com/ufal/udpipe). The package is available under the Mozilla Public License Version 2.0. Installation can be done as follows. Please visit the package documentation at https://bnosac.github.io/udpipe/en and look at the R package vignettes for further details.

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