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MALLET is an integrated collection of Java code useful for statistical natural language processing, document classification, cluster analysis, information extraction, topic modeling and other machine learning applications to text.
General Architecture for Text Engineering (GATE) is a Java suite of natural language processing (NLP) tools for man tasks, including information extraction in many languages. [1] It is now used worldwide by a wide community of scientists, companies, teachers and students. It was originally developed at the University of Sheffield beginning in 1995.
Natural-language programming (NLP) is an ontology-assisted way of programming in terms of natural-language sentences, e.g. English. [1] A structured document with Content, sections and subsections for explanations of sentences forms a NLP document, which is actually a computer program .
ML.NET was developed to aid integration with existing .NET projects, simplifying the process for existing software using the .NET platform. Smalltalk has been used extensively for simulations, neural networks, machine learning, and genetic algorithms. It implements a pure and elegant form of object-oriented programming using message passing.
Spark NLP for Healthcare is a commercial extension of Spark NLP for clinical and biomedical text mining. [10] It provides healthcare-specific annotators, pipelines, models, and embeddings for clinical entity recognition, clinical entity linking, entity normalization, assertion status detection, de-identification, relation extraction, and spell checking and correction.
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 language detection, tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing and coreference resolution.
Karel is an educational programming language for beginners, created by Richard E. Pattis in his book Karel The Robot: A Gentle Introduction to the Art of Programming. Pattis used the language in his courses at Stanford University, California. The language is named after Karel Čapek, a Czech writer who introduced the word robot in his play R.U ...
In-context learning, refers to a model's ability to temporarily learn from prompts.For example, a prompt may include a few examples for a model to learn from, such as asking the model to complete "maison → house, chat → cat, chien →" (the expected response being dog), [23] an approach called few-shot learning.
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