Retext is an ecosystem of plugins that work with natural language as structured data, specifically concrete syntax trees. It is a tool that transforms natural language with plugins, which can inspect and change the natural language. The repository is a monorepo containing packages for parsing English, Dutch and Latin-script prose and serializing syntax trees.
MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text. It includes tools for converting text to features, classifiers such as Naïve Bayes, Maximum Entropy and Decision Trees, sequence tagging with Hidden Markov Models and Conditional Random Fields, and sampling-based topic model implementations.
KoNLPy (pronounced "ko en el PIE") is a Python package for natural language processing of the Korean language. It is open source software released under GPL v3 or above, and users are asked to acknowledge its use with a citation.
OpenFace is a free and open source face recognition implementation with deep neural networks, written in Python and Torch and based on the CVPR 2015 FaceNet paper. It detects faces, aligns them, and embeds faces on a 128-dimensional unit hypersphere.
Apache OpenNLP is a machine learning based toolkit for the processing of natural language text. It supports tasks such as sentence segmentation, tokenization, lemmatization, part-of-speech tagging, named entity extraction, chunking, parsing, language detection and coreference resolution. The project is developed by volunteers and welcomes contributions, from small documentation fixes to new components.
Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters. It provides high-level APIs in Java, Scala, Python and R, and supports Spark SQL, pandas API on Spark, MLlib, GraphX and Structured Streaming. The documentation covers downloads, the shell and client applications.
Licensing is neither feasible nor effective for addressing AI risks provides machine-learning models, research, training resources, or evaluation…
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MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text. It includes tools for converting text to features, classifiers such as Naïve Bayes, Maximum Entropy and Decision Trees, sequence tagging with Hidden Markov Models and Conditional Random Fields, and sampling-based topic model implementations.
KoNLPy (pronounced "ko en el PIE") is a Python package for natural language processing of the Korean language. It is open source software released under GPL v3 or above, and users are asked to acknowledge its use with a citation.
OpenFace is a free and open source face recognition implementation with deep neural networks, written in Python and Torch and based on the CVPR 2015 FaceNet paper. It detects faces, aligns them, and embeds faces on a 128-dimensional unit hypersphere.
Apache OpenNLP is a machine learning based toolkit for the processing of natural language text. It supports tasks such as sentence segmentation, tokenization, lemmatization, part-of-speech tagging, named entity extraction, chunking, parsing, language detection and coreference resolution. The project is developed by volunteers and welcomes contributions, from small documentation fixes to new components.
Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters. It provides high-level APIs in Java, Scala, Python and R, and supports Spark SQL, pandas API on Spark, MLlib, GraphX and Structured Streaming. The documentation covers downloads, the shell and client applications.
Licensing is neither feasible nor effective for addressing AI risks provides machine-learning models, research, training resources, or evaluation…
