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This project analyzes IMDb movie reviews to classify sentiments as positive or negative. It includes text preprocessing, feature extraction using TF-IDF and CountVectorizer, training Logistic Regression and Naive Bayes classifiers, and visualizing frequent words with WordClouds.
Named Entity Recognition (NER) on news articles using rule-based and spaCy models. Includes entity extraction, visualizations with displaCy, and comparison of small vs large spaCy models for analysis and insights.
Fake News Detection system using NLP techniques and TF-IDF vectorization to classify news articles as real or fake. Trained with Logistic Regression and SVM on the Fake and Real News Dataset, with preprocessing, evaluation metrics, and word cloud visualizations.
News Category Classification using AG News dataset. Implements text preprocessing, TF-IDF vectorization, and trains Logistic Regression and a Neural Network to classify news into World, Sports, Business, and Sci/Tech categories. Includes data visualization and model evaluation.
A PDF Reader application powered by AI, allowing users to upload PDF documents and extract meaningful information using advanced NLP models. Built with Streamlit, Transformers, and Langchain, this app provides a seamless interface for interacting with and analyzing PDF content.
PropInsight is an AI-powered property inspection report generator that utilizes LLM models to analyze property types and observed issues, generating comprehensive and data-driven reports for smarter decision-making.
Companion repository for the paper "Methodological Trends in Psychology Research: Analyzing Abstracts with NLP and Machine Learning." Includes code, term glossary, and workflows for clustering and text analysis.