Smile (Statistical Machine Intelligence and Learning Engine) is a fast and comprehensive machine learning, NLP, linear algebra, graph, interpolation, and visualization system in Java and Scala. With advanced data structures and algorithms, Smile delivers state-of-art performance.Smile covers every aspect of machine learning, including classification, regression, clustering, association rule mining, feature selection, manifold learning, multidimensional scaling, genetic algorithms, missing value imputation, efficient nearest neighbor search, etc.

Smile - Statistical Machine Intelligence & Learning Engine

JARVIS on Messenger is Just A Rather Very Intelligent System, now on Messenger!

JARVIS-on-Messenger - A community-driven python bot that aims to be as simple as possible to serve humans with their everyday tasks

LanguageTool is an Open Source proofreading software for English, French, German, Polish, Russian, and more than 20 other languages. It finds many errors that a simple spell checker cannot detect. Receive tips on how to improve your text (including punctuation advice etc.) while typing an e-mail, a blog post or just a simple tweet. Whatever language you're using, LanguageTool will automatically detect it and provide suggestions. 

LanguageTool - Style and Grammar Checker for 25+ Languages

SentencePiece is an unsupervised text tokenizer and detokenizer mainly for Neural Network-based text generation systems where the vocabulary size is predetermined prior to the neural model training. SentencePiece implements subword units (e.g., byte-pair-encoding (BPE) and unigram language model with the extension of direct training from raw sentences. SentencePiece allows us to make a purely end-to-end system that does not depend on language-specific pre postprocessing.
 
SentencePiece is a re-implementation of sub-word units, an effective way to alleviate the open vocabulary problems in neural machine translation. Neural Machine Translation models typically operate with a fixed vocabulary. Unlike most unsupervised word segmentation algorithms, which assume an infinite vocabulary, SentencePiece trains the segmentation model such that the final vocabulary size is fixed, e.g., 8k, 16k, or 32k.

SentencePiece is an unsupervised text tokenizer and detokenizer mainly for Neural Network-based text generation systems where the vocabulary size is predetermined prior to the neural model training. SentencePiece implements subword units (e.g., byte-pair-encoding (BPE) and unigram language model with the extension of direct training from raw sentences. SentencePiece allows us to make a purely end-to-end system that does not depend on language-specific pre  postprocessing.

SentencePiece - Unsupervised text tokenizer for Neural Network-based text generation

WinkNLP is a JavaScript library for Natural Language Processing (NLP). Designed specifically to make development of NLP applications easier and faster, winkNLP is optimized for the right balance of performance and accuracy. It is built ground up with a lean code base that has no external dependency. It has full Typescript support and runs on Node.js and browsers.
WinkNLP has a comprehensive natural language processing (NLP) pipeline covering tokenization, sentence boundary detection (sbd), negation handling, sentiment analysis, part-of-speech (pos) tagging, named entity recognition (ner), custom entities recognition (cer). WinkNLP can easily process large amount of raw text at speeds over 650,000 tokens/second &nbsp;on a M1 Macbook Pro in both browser and Node.js environments. It even runs smoothly on a low-end smartphone's browser.
WinkNLP can process multilingual text string, identifies the boundary of different languages in the string. It comes with pre-trained language models for Sentence Boundary Detection, Sentiment Analysis, Part-of-speech tagging.&nbsp;
<pre class="language-bash"><code>npm install wink-nlp --save</code></pre>

WinkNLP is a JavaScript library for Natural Language Processing (NLP). Designed specifically to make development of NLP applications easier and faster, winkNLP is optimized for the right balance of performance and accuracy.

WinkNLP - Developer friendly Natural Language Processing

Mycroft is an Artificial intelligence for everyone. It  
uses open software to process natural language, determine your intent and take action. It can integrate a host of professional functions – Control scenes to conserve power, grant office access with your voice. It can control all of your media and devices with the sound of your voice.   Adjust your thermostat, turn on your lights, water your lawn, play your favorite movie and lot more.

Mycroft -  an Artificial intelligence for everyone 

Rasa is an open source machine learning framework to automate text-and voice-based conversations. With Rasa, you can build chatbots on Facebook, Slack, Microsoft Bot Framework, Rocket.Chat, Mattermost, Telegram etc. Rasa's primary purpose is to help you build contextual, layered conversations with lots of back-and-forth. To have a real conversation, you need to have some memory and build on things that were said earlier. Rasa lets you do that in a scalable way.

Rasa - Create chatbots and voice assistants

Stanza is a Python NLP Library for Many Human Languages. It contains support for running various accurate natural language processing tools on 60+ languages and for accessing the Java Stanford CoreNLP software from Python. A new collection of biomedical and clinical English model packages are now available, offering seamless experience for syntactic analysis and named entity recognition (NER) from biomedical literature text and clinical notes.

Stanza - A Python NLP Library for Many Human Languages

AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy machine learning and deep learning models on image, text, and tabular data.
 
<ul>
<li>Quickly prototype deep learning and classical ML solutions for your raw data with a few lines of code.</li>
<li>Automatically utilize state-of-the-art techniques (where appropriate) without expert knowledge.</li>
<li>Leverage automatic hyperparameter tuning, model selection/ensembling, architecture search, and data processing.</li>
<li>Easily improve/tune your bespoke models and data pipelines, or customize <cite>AutoGluon</cite> for your use-case.</li>
</ul>

AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy machine learning and deep learning models on image, text, and tabular data.

AutoGluon - AutoML for Text, Image, and Tabular Data

The 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. 
 
The Apache OpenNLP library contains several components, enabling one to build a full natural language processing pipeline. These components include: sentence detector, tokenizer, name finder, document categorizer, part-of-speech tagger, chunker, parser, coreference resolution. Components contain parts which enable one to execute the respective natural language processing task, to train a model and often also to evaluate a model. Each of these facilities is accessible via its application program interface (API). In addition, a command line interface (CLI) is provided for convenience of experiments and training.

 The 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. 

OpenNLP -  Machine learning based toolkit for the processing of natural language text

WantWords is an open-source online reverse dictionary. Reverse dictionary is  an opposite to a regular (forward) dictionary that provides definitions for query words, a reverse dictionary returns words semantically matching the query descriptions. 

WantWords - An open-source online reverse dictionary

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.

Language Detection - Language Detection Library in Java

Obsei is a low code AI powered automation tool. It can be used in various business flows like social listening, AI based alerting, brand image analysis, comparative study and more. 
It consist of Observer, Analyzer and Informer. Observer observes the platform like Twitter, Facebook, App Stores, Google reviews, Amazon reviews, News, Website etc and feed that information. Analyzer performs text analysis like classification, sentiment, translation, PII on the analyzed data. Informer sends it to ticketing system, data store, dataframe etc for further action and analysis.

Obsei - Low code AI powered automation tool

Rubrix is a production-ready Python framework for exploring, annotating, and managing data in NLP projects.
Most annotation tools treat data collection as a one-off activity at the beginning of each project. In real-world projects, data collection is a key activity of the iterative process of ML model development. Once a model goes into production, you want to monitor and analyze its predictions, and collect more data to improve your model over time. Rubrix is designed to close this gap, enabling you to iterate as much as you need.

RUBRIX -  Python framework to explore, label, and monitor data for NLP

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Smile - Statistical Machine Intelligence & Learning Engine

JARVIS-on-Messenger - A community-driven python bot that aims to be as simple as possible to serve humans with their everyday tasks

LanguageTool - Style and Grammar Checker for 25+ Languages

SentencePiece - Unsupervised text tokenizer for Neural Network-based text generation

WinkNLP - Developer friendly Natural Language Processing

Mycroft - an Artificial intelligence for everyone

Rasa - Create chatbots and voice assistants

Stanza - A Python NLP Library for Many Human Languages

AutoGluon - AutoML for Text, Image, and Tabular Data

OpenNLP - Machine learning based toolkit for the processing of natural language text

WantWords - An open-source online reverse dictionary

Language Detection - Language Detection Library in Java

Obsei - Low code AI powered automation tool

RUBRIX - Python framework to explore, label, and monitor data for NLP

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