Naina Naina

Fake News Detector | Machine Learning Project Developed a machine learning-based application to classify news articles as Real or Fake. Preprocessed and analyzed text data using techniques such as tokenization, stop-word removal, and TF-IDF vectorization. Trained and evaluated a classification model to identify potentially misleading or false news. Built a simple user interface where users can enter news content and receive a prediction.

Accident Prediction System | Python, Machine Learning Developed an AI/ML-based system to predict the likelihood of road accidents using historical accident and environmental data. Performed data preprocessing, feature selection, and exploratory data analysis to identify factors associated with accident occurrence. Trained and evaluated machine learning classification models to predict accident risk based on input conditions. Built a user-friendly prediction interface that provides an accident-risk prediction based on the entered parameters.

Secure File Upload & Malware Scanning Portal | Python, Flask, Cybersecurity Developed a secure web-based portal for file uploading and malware detection to reduce the risk of malicious files entering a system. Implemented file validation, extension/type checking, size restrictions, and secure upload handling to prevent unsafe file uploads. Integrated malware scanning to analyze uploaded files and identify potentially malicious or suspicious content. Designed a user-friendly interface to display upload status, scan results, and security alerts. Applied basic cybersecurity practices such as input validation, access control, and secure file storage.