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A complete NLP and Machine Learning project to detect fake and real news using TF-IDF and Logistic Regression. Includes full training pipeline, evaluation charts, and an interactive Streamlit web app for real-time credibility analysis. Dataset adapted from Kaggle’s Fake and Real News Dataset.
This repository contains a Python script that performs sentiment analysis on news articles related to Binance Coin (BNB). It fetches news articles from the CryptoCompare API and utilizes the Groq AI language model to analyze the sentiment of each article's title and body. The script classifies the sentiment as positive, negative, or neutral, and th
An auto-refreshing dataset of major news domains and their X (formerly Twitter) accounts, complete with real-time stats like follower counts and engagement metrics. Made for tracking media trends and analytics at scale.
Train a model to categorize news articles, scrape and translate articles, and predict their categories using TensorFlow, Keras, and Google Translate API.
Tool that allows characterizing territorial issues through news processing. It performs topic clustering, sentiment analysis, and data analysis using BERTopic & ChatGPT.
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.