This is a language detection library implemented in plain Java. It detects language of a text using naive Bayesian filter. It is 99% over precision for 53 languages.
https://github.com/shuyo/language-detectionTags | language-identification language-detection natural-language-processing nlp |
Implementation | Java |
License | Apache |
Platform | OS-Independent |
Detect the language of text.† - Based on the UDHR, the most translated document in the world.
natural-language language-detection nlp natural language detection detectMalaya is a Natural-Language-Toolkit library for bahasa Malaysia, powered by Deep Learning Tensorflow. Only Python 3.6.0 and above and Tensorflow 1.15.0 and above are supported.
natural-language-processing sentiment-analysis tensorflow language-detection entity-framework normalizer ner emotion-analysis pos-tagging malay bahasa-malaysia subjectivity-analysis malay-nlpPyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks such as the extraction of n-grams and frequency lists, and to build simple language model. There are also more complex data types and algorithms. Moreover, there are parsers for file formats common in NLP (e.g. FoLiA/Giza/Moses/ARPA/Timbl/CQL). There are also clients to interface with various NLP specific servers. PyNLPl most notably features a very extensive library for working with FoLiA XML (Format for Linguistic Annotatation). The library is a divided into several packages and modules. It works on Python 2.7, as well as Python 3.
nlp computational-linguistics linguistics library folia machine-learning language-modelling search-algorithms evaluation-metrics text-processing nlp-library natural-language-processingWelcome to my GitHub repo. I am a Data Scientist and I code in R, Python and Wolfram Mathematica. Here you will find some Machine Learning, Deep Learning, Natural Language Processing and Artificial Intelligence models I developed.
anomaly-detection deep-learning autoencoder keras keras-models denoising-autoencoders generative-adversarial-network glove keras-layer word2vec nlp natural-language-processing sentiment-analysis opencv segnet resnet-50 variational-autoencoder t-sne svm-classifier latent-dirichlet-allocationThe Apache OpenNLP library is a machine learning based toolkit for the processing of natural language text. It supports the most common NLP tasks, such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing, and coreference resolution. These tasks are usually required to build more advanced text processing services. OpenNLP also includes maximum entropy and perceptron based machine learning.
nlp natural-language-processing machine-learning parts-of-speech categorization auto-tagging sentence-detector🤗 Transformers provides thousands of pretrained models to perform tasks on texts such as classification, information extraction, question answering, summarization, translation, text generation and more in over 100 languages. Its aim is to make cutting-edge NLP easier to use for everyone. 🤗 Transformers provides APIs to quickly download and use those pretrained models on a given text, fine-tune them on your own datasets and then share them with the community on our model hub. At the same time, each python module defining an architecture is fully standalone and can be modified to enable quick research experiments.
nlp natural-language-processing tensorflow pytorch transformer speech-recognition seq2seq flax gpt pretrained-models language-models natural-language-generation nlp-library language-model bert natural-language-understanding jax xlnet pytorch-transformers model-hubJohn Snow Labs Spark-NLP is a natural language processing library built on top of Apache Spark ML. It provides simple, performant & accurate NLP annotations for machine learning pipelines, that scale easily in a distributed environment. This library has been uploaded to the spark-packages repository https://spark-packages.org/package/JohnSnowLabs/spark-nlp .
nlp nlu natural-language-processing natural-language-understanding spark spark-ml pyspark machine-learning named-entity-recognition sentiment-analysis lemmatizer spell-checker tokenizer entity-extraction stemmer part-of-speech-tagger annotation-frameworkNLP Architect is an open-source Python library for exploring state-of-the-art deep learning topologies and techniques for natural language processing and natural language understanding. It is intended to be a platform for future research and collaboration. Framework documentation on NLP models, algorithms, and modules, and instructions on how to contribute can be found at our main documentation site.
deeplearning nlp nlu tensorflow dynet kerasNTextCat is text classification utility. Primary target is language identification. So it helps you to recognize (identify) the language of text (or binary) snippet. Pure .net application (C#).
categorization classification identification language language-processing natural-language nlpThis curated list comprises awesome resources, libraries, information sources about computational processing of texts in human languages with the Ruby programming language. That field is often referred to as NLP, Computational Linguistics, HLT (Human Language Technology) and can be brought in conjunction with Artificial Intelligence, Machine Learning, Information Retrieval, Text Mining, Knowledge Extraction and other related disciplines. This list comes from our day to day work on Language Models and NLP Tools. Read why this list is awesome. Our FAQ describes the important decisions and useful answers you may be interested in.
machine-learning natural-language-processing nlp sentiment-analysis pos-tag awesome awesome-list list computational-linguistics rubynlp rubymlThis project collects a number of core libraries for Natural Language Processing (NLP) developed by Cognitive Computation Group. Each library contains detailed readme and instructions on how to use it. In addition the javadoc of the whole project is available here.
natural-language-processing nlp big-data natural-language data-mining cogcompI've been working on several natural language processing tasks for a long time. One day, I felt like drawing a map of the NLP field where I earn a living. I'm sure I'm not the only person who wants to see at a glance which tasks are in NLP. Reviewed and updated by YJ Choe on Oct. 18, 2017.
language natural-language-processing nlpThis document aims to track the progress in Natural Language Processing (NLP) and give an overview of the state-of-the-art (SOTA) across the most common NLP tasks and their corresponding datasets. It aims to cover both traditional and core NLP tasks such as dependency parsing and part-of-speech tagging as well as more recent ones such as reading comprehension and natural language inference. The main objective is to provide the reader with a quick overview of benchmark datasets and the state-of-the-art for their task of interest, which serves as a stepping stone for further research. To this end, if there is a place where results for a task are already published and regularly maintained, such as a public leaderboard, the reader will be pointed there.
NLP Architect is an open source Python library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing and Natural Language Understanding Neural Networks. NLP Architect is an NLP library designed to be flexible, easy to extend, allow for easy and rapid integration of NLP models in applications and to showcase optimized models.
nlp deep-learning tensorflow nlu transformers pytorch deeplearning quantization bert dynetspaCy is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. spaCy comes with pre-trained statistical models and word vectors, and currently supports tokenization for 20+ languages. It features the fastest syntactic parser in the world, convolutional neural network models for tagging, parsing and named entity recognition and easy deep learning integration. It's commercial open-source software, released under the MIT license. 💫 Version 2.0 out now! Check out the new features here.
natural-language-processing data-science big-data machine-learning cython nlp artificial-intelligence ai spacy nlp-library neural-network neural-networks deep-learningAI Tool for querying natural language on tabular data.Built using QA models from transformers.
nlp qa machine-learning csv sql database ai tabular-data sql-query question-answering sql-generation nl2sql tableqa table-qa querying-natural-languageThis repository contains the lecture slides and course description for the Deep Natural Language Processing course offered in Hilary Term 2017 at the University of Oxford. This is an applied course focussing on recent advances in analysing and generating speech and text using recurrent neural networks. We introduce the mathematical definitions of the relevant machine learning models and derive their associated optimisation algorithms. The course covers a range of applications of neural networks in NLP including analysing latent dimensions in text, transcribing speech to text, translating between languages, and answering questions. These topics are organised into three high level themes forming a progression from understanding the use of neural networks for sequential language modelling, to understanding their use as conditional language models for transduction tasks, and finally to approaches employing these techniques in combination with other mechanisms for advanced applications. Throughout the course the practical implementation of such models on CPU and GPU hardware is also discussed.
deep-learning machine-learning natural-language-processing nlp oxfordTextCat written in Perl helps to identify 69 natural langauge.
language-identification language-detection text-catagorizationA Machine Learning library written in pure Go designed to support relevant neural architectures in Natural Language Processing. spaGO is self-contained, in that it uses its own lightweight computational graph framework for both training and inference, easy to understand from start to finish.
nlp machine-learning natural-language-processing deep-learning neural-network automatic-differentiation artificial-intelligence recurrent-networks lstm computation-graph question-answering bart automatic-translation deeplearning language-model bert transformer-architecture bert-as-service named-entities-recognitionPlease read the contribution guidelines before contributing. Please feel free to create pull requests.
natural-language-processing deep-learning machine-learning language awesome awesome-list nlp text-mining
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