github link: https://github.com/IamAbhinav01/Next-Word-Prediction-Using-LSTM Built and deployed an LSTM-based model to predict the next word in a sentence using conversational text data. The model was trained on tokenized sequences from the Cornell Movie Dialogues Corpus, learning contextual relationships in natural language. A Streamlit-based web interface allows real-time predictions from users. Key Highlights: Used sequence padding and one-hot encoding for training Trained for 5 epochs using categorical cross-entropy loss Achieved 18.46% validation accuracy with val_loss: 5.1