Ultra-lightweight MobileNetV3 model optimized for on-device NSFW detection and bias-free content moderation for african social network.
Hush: A lightweight, context-aware text toxicity classifier. Leveraging NLP and Random Forest ensemble learning to detect and mitigate harmful language in real-time. Built for efficiency, safety, and cleaner digital communication.
🛡️ A comprehensive web application built with Next.js for conducting systematic risk evaluations and root cause analysis. Features multi-step forms for project data collection, potential hazard assessment, immediate and basic cause identification, and corrective action planning.
ML-powered YouTube scanner detecting potential doxxing content targeting K-pop idols (TF-IDF + Flask dashboard)
Train and optimize AI model behavior with configurable limit constraints.
Preview, validate, apply, and undo large file-renaming operations with a reviewable manifest.
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