AI project: Hate Speech Detection in Transliterated Amharic Text (content moderation / text classification)
Built and trained a machine learning text classification pipeline for hate speech detection in transliterated Amharic (Amharic in Latin script). Gathered, normalized, and preprocessed raw social media datasets to address high linguistic variation and lack of standardized spelling. Evaluated the trained model using precision, recall, and F1-scores to measure classification performance. • Data preprocessing and normalization for noisy transliterated text • Supervised text classification pipeline construction from scratch • Performance evaluation using precision/recall/F1 metrics • Content moderation and online safety use case for low-resource language data