Kaggle Gold Medal (13th Place) Submission to Google's LLM Prompt Recovery Challenge
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Updated
Oct 10, 2024 - Python
Kaggle Gold Medal (13th Place) Submission to Google's LLM Prompt Recovery Challenge
This is my final year project "customer reviews classification and analysis system using data mining and nlp". It analyzes and then classifies the customer reviews on the basis of their fakeness, sentiments, contexts and topics discussed. The reviews are taken from various e-commerce platforms like daraz and amazon.
A modular, automated Python pipeline to extract insights from policy documents using NLP and LLM techniques. The goal of the project is to provide policymakers, researchers, and institutions with comprehensive insights into how different organizations are managing and regulating the use of Generative AI.
BERTopic and Causal Discovery Analysis on Mental Health Dataset: Exploring Factors Affecting Mental Health Issues
Customer reviews topic modeling with BERTopic
Course materials on computational text analysis. John McLevey. 2024. Introduction to Computational Social Science with Python. GESIS Fall Seminar in Computational Social Science.
Analysis of Chinese Financial Discourse Based on Topic Clustering and Emotional Evolution | Fall 2023 - Spring 2024
Unveiling Sentiments and Topics in COVID-19 Vaccine Comments on YouTube Over Time: from the First Vaccine Approval to the Post-Pandemic Era
Build interactive topic modeling pipelines.
Unsupervised Topic Modeling via BERTopic
Topic Modeling of scientific papers using BERTopic.
Topic modeling is a text mining 🔱 technique in which an algorithm is applied to a large corpus of documents that identifies patterns of word co-occurrence. These patterns of word co-occurrence are conceptualized as “topics” which can be used to discover latent structures in the corpus, to group similar documents together.
A Project on Temporal Topic Modeling
NLP: topic modelling using BERTopic + LSA + pLSA + LDA
A machine learning pipeline for detecting Slovenian political bias based on sentiment towards various topics and political parties.
Adapted BERTopic pipeline for Topic Modeling the arXiv dataset
Submission for CL4HEALTH @ LREC-COLING 2024
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