This project explores emotion classification in social media texts using multiple text representation techniques (TF-IDF, Word2Vec, GloVe) and deep recurrent neural networks (GRU, LSTM, Bi-GRU, Bi-LSTM). The best model achieved an F1-Score of 0.9248, with Word2Vec and Bi-LSTM outperforming other combinations.

Emotion classification iOS app using CoreML and SwiftUI – demo for sentiment and emotion analysis, with the model converted from Scikit-learn using coremltools.

😊 Classify emotions in text using a CoreML model in this iOS app, built with SwiftUI and MVVM architecture for efficient performance and modern development.