NLP related concepts, challenges and datasets
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Updated
Jul 16, 2019 - Jupyter Notebook
NLP related concepts, challenges and datasets
📑Semantic content similarity search experiment on heartfulness.org mission literature dataset. Developed using pytorch and azure machine learning service.
Container-first, JSON-configurable, NLP REST service based on Flair
FewClick-TrainAndHost is a platform to auto train a text classification model and later convert it to a flask based web-app in just few clicks.
A deep learning approach for detecting sarcasm in Headlines
My code and research while exploring NLP fake news detection under an internship.
📜 Dehyphenation of broken text (mainly German), i.e., extracted from a PDF
Code and data for paper 'Causality extraction based on self-attentive BiLSTM-CRF with transferred embeddings'
ANTILLES : An Open French Linguistically Enriched Part-of-Speech Corpus
pretrained transformer and embeddings language models
Large Scale benchmarking of state of the art text vectorizers
A StackExchange flair react component
In the wild extraction of entities that are found using Flair and displayed using a very elegant front-end.
embeddings language models
Use of State of the Art FLAIR library for the NLP datasets
An overview of the possibilities of using TARS models for low language resources
Text2Emoji helps you add necessary emojis to your text by analysing the emotion behind the writing.
This repository contains my scripts, results and visualization for my bachelor thesis "Medical concept PROBLEM: Polarity, Modality and Temporal Relations" - ON GOING, doing some code reorganize
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