A Toolkit for Industrial Topic Modeling
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Updated
Aug 28, 2017 - C++
Natural language processing (NLP) is a field of computer science that studies how computers and humans interact. In the 1950s, Alan Turing published an article that proposed a measure of intelligence, now called the Turing test. More modern techniques, such as deep learning, have produced results in the fields of language modeling, parsing, and natural-language tasks.
A Toolkit for Industrial Topic Modeling
Text processing library for natural language processing.
Generating Monty Python scripts
latent dirichlet allocation (topic modeling) implementations for hpc and cloud systems
RNNLM Toolkit
NMT developed by Qiang
Final graduation project. Working on short text topic identification.
Лабораторные работы по курсу «Компьютерная лингвистика-1» (ФИТ НГУ, 2022).
MITIE: library and tools for information extraction
Text language detector based on n-grams
Automatically identify the subject of posts from the EECS 280 Piazza using natural language processing and machine learning techniques.
A spelling corrector written in C++.
Bigram-based clustering for language modelling
Corpus and Vocabulary Preprocessing Utilities for Natural Language Pipelines
Unsupervised text tokenizer for Neural Network-based text generation.
Experimental HPC accelerated deep Learning research, a next-gen R&D AI project with Scala API. 🚀
SLING - A natural language frame semantics parser
C++ Implementation for Affinity Propagation
Created by Alan Turing