Custom classifiers to detect sexist language.
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Updated
Feb 11, 2021 - Jupyter Notebook
Custom classifiers to detect sexist language.
Analyze user comments through Natural Language Processing (NLP) techniques and Analyze sexism dataset
Explainable Machine Learning in Linguistics and Applied NLP: Two Case Studies of Norwegian Dialectometry and Sexism Detection in French Tweets
Ghast farming addon for Meteor Client
The project focuses on identifying signs of sexism in texts through three tasks: identifying sexism, categorizing sexism, and sub-categorizing sexism. The best model used for completing these tasks is RoBERTa pre-trained on hate speech with the addition of data augmentation and learning rate scheduler techniques.
Submission for SemEval 2023 Task 10 EDOS
Solution using adversarial training for the explainable detection of sexism in social networks (EDOS) task as part of SEMEVAL 2023
Human Language Technologies (HLT) project. Computer Science Master Degree, University of Pisa. A.Y 2023/2024
A terminal based game about privileges. Build in the context of the Basic Programming M2 course at Systax Institute.
Task 10: Explainable Detection of Online Sexism
Benchmark tool aimed at evaluating biases of large language models
Bengali Misogyny Identification with Deep Learning and LIME.
Hackathon for an NLP task involving sexism classification
Notebooks and papers of the Penta ML and NLP teams in the Exist 2024 challenge at CLEF 2024
Text classification with ngrams for Natural Language Processing case study @ Università degli Studi di Bari Aldo Moro, AY 2023/24
Smashing Sexism: Overcoming Bias in a Cross-Domain 5-Point Classification Challenge
This project is an individual task as a part of the coursework from CSE712: Symbolic Machine Learning-II. Here I applied a neural network approach to address the task of detecting online sexism. Specifically, by utilizing natural language processing (NLP) methods to analyze textual data and build predictive models.
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