Metadata-Version: 1.1
Name: malaya
Version: 0.9
Summary: Natural-Language-Toolkit for bahasa Malaysia, powered by Deep Learning.
Home-page: https://github.com/DevconX/Malaya
Author: huseinzol05
Author-email: husein.zol05@gmail.com
License: UNKNOWN
Download-URL: https://github.com/DevconX/Malaya/archive/master.zip
Description: .. figure:: https://raw.githubusercontent.com/DevconX/Malaya/master/session/towns-of-malaya.jpg
        
        |Downloads| |Latest Version| |Build Status| |Documentation Status|
        
        .. |Downloads| image:: https://img.shields.io/pypi/dm/malaya.svg
           :target: https://pypi.python.org/pypi/malaya
        .. |Latest Version| image:: https://badge.fury.io/py/malaya.svg
           :target: https://pypi.python.org/pypi/malaya
        .. |Build Status| image:: https://travis-ci.org/huseinzol05/Malaya.svg?branch=master
           :target: https://travis-ci.org/huseinzol05/Malaya
        .. |Documentation Status| image:: https://readthedocs.org/projects/malaya/badge/?version=latest
           :target: https://malaya.readthedocs.io/
        
        Natural-Language-Toolkit for bahasa Malaysia, powered by Deep Learning
        Tensorflow.
        
        -  Free software: MIT license
        -  Documentation: https://malaya.readthedocs.io/
        
        Features
        --------
        
        -  **Entities Recognition**, using latest state-of-art CRF deep learning
           models to do Naming Entity Recognition.
        -  **Language Detection**, using various machine learning models to distinguish Malay, English, and Indonesian.
        -  **Normalizer**, using local Malaysia NLP researches to normalize any
           bahasa texts.
        -  Num2Word
        -  **Part-of-Speech Recognition**, using latest state-of-art CRF deep
           learning models to do POS Recognition.
        -  **Sentiment Analysis**, from BERT, Fast-Text, Dynamic-Memory Network,
           Attention to build deep sentiment analysis models.
        -  **Spell Correction**, using local Malaysia NLP researches to
           auto-correct any bahasa words.
        -  Stemmer
        -  **Summarization**, using skip-thought state-of-art to give precise
           summarization.
        -  **Topic Modelling**, provide LDA2Vec, LDA, NMF and LSA interface for easy topic modelling.
        -  **Topic and Influencers Analysis**, using deep and machine learning
           models to understand topics and Influencers similarity in sentences.
        -  **Toxicity Analysis**, from BERT, Fast-Text, Dynamic-Memory Network,
           Attention to build deep Toxic Multi-label analysis models.
        -  Word2Vec
        
        Contributors
        ------------
        
        -  **Husein Zolkepli** - *Initial work* - `huseinzol05`_
        
        -  **Sani** - *build PIP package* - `khursani8`_
        
        .. _Malaya Wiki: https://github.com/DevconX/Malaya/wiki
        .. _huseinzol05: https://github.com/huseinzol05
        .. _khursani8: https://github.com/khursani8
        
Keywords: nlp,bm
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Text Processing
