Movie Genre Classification (ML model training using labeled dataset)
Built a machine learning genre classification pipeline using labeled movie description data. Used TF-IDF features and logistic regression to train a model that predicts the target genre class for each record. Prepared prediction outputs for a submission file mapping each record id to a predicted genre label. • Inferred text preprocessing steps including lowercase conversion, HTML removal, and cleaning special characters and numbers • Created TF-IDF vectorization features with n-grams (1,2), English stop-word removal, and a max feature cap • Trained a logistic regression classifier with specified iteration and random state settings • Generated predictions for test records and formatted results as id|genre