summaries of all the papers I read
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Updated
Jul 9, 2024
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.
summaries of all the papers I read
Natural Language Processing Courses with Resources
A collection of Colab/Jupyter Notebooks for NLP, collection, analysis, and visualization.
A collection of corpora for named entity recognition (NER) and entity recognition tasks. These annotated datasets cover a variety of languages, domains and entity types.
Portuguese pre-trained BERT models
The hands-on NLTK tutorial for NLP in Python
Predicting the next word for a sentence/word given using BERT
Hub for the Portuguese language NLP Resources
A lexicon for Sudachi
A Dutch RoBERTa-based language model
Romanian multidomain human-machine dataset and detection of machine generated text
Repository for the LREC-COLING 2024 Paper: Persona-Based Corpus in the Diabetes Mellitus Domain – Applying a Human-Centered Approach to a Low-Resource Context
A list of Romanian NLP Datasets
This repository contains code and datasets related to entity/knowledge papers from the VERT (Versatile Entity Recognition & disambiguation Toolkit) project, by the Knowledge Computing group at Microsoft Research Asia (MSRA).
This repository consist of projects related to Natural Language Processing using machine learning and deep learning concepts
Twitter-Sentiment-Analysis-NLP-Project
The easiest way to get n-grams from strings!
Python program for detecting unintentional bilingual and translation instances in NLP datasets.
Projects and useful articles / links
Interactive Odin tutorial
Created by Alan Turing