Natural language processing (NLP) is a branch of artificial intelligence that helps computers understand, interpret and manipulate human language.
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Updated
Jul 29, 2023 - Jupyter Notebook
Natural language processing (NLP) is a branch of artificial intelligence that helps computers understand, interpret and manipulate human language.
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
This is the official implementation of our paper Robust Hate Speech Detection via Mitigating Spurious Correlations (Tiwari et al., AACL-IJCNLP 2022)
Deep Learning from basic to advance level include Bert for text intent classification
Application interface that use a pre-trained model based on BERT to extract information from aviation accidents texts. Laboratory Assignment II: Trainable Information Extraction. From AIW 2021.
FastAPI application for language detection
This project compares the performance of a Naive Bayes model and fine-tuned BERT models on emotion classification from text.
Completed as part of the "Natural Language Processing" course, this project employs the ArcEager parsing algorithm. Implementation is carried out using PyTorch and the Hugging Face library for utilizing pretrained BERT models.
DACON 기후기술분류 경진대회 at @KNU-BrainAI (2021)
This repository contains all the programming assignments for the Applied Natural Language Processing class at the University of Southern California in the Spring 2022 semester.
Transfer Learning for News Headline Sarcasm Detection Using BERT Based Supervised Fine-Tuning
Predict readability of passages using Robustly Optimised BERT Pre-trained Approach.
Repo to contains NLP project where a BERT model is fine-tuned on spam classification task
Analysis of Hotel Booking Cancellation dataset using statistical model and provide predictions on future booking cancelations using Logistic regression model.
Successfully developed a fine-tuned BERT transformer model which can accurately classify symptoms to their corresponding diseases upto an accuracy of 89%.
In this project we have tried to do multi-label hate-speech classification in Bengali and Hindi language using fill-mask transformer models.
Pre-training and fine tuning BERT models
Performing Text Extraction also known as Question-Answering using BERT,and serving it Via REST API.
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