This project dives into the analysis and generation of lyrics from Portishead's discography. By leveraging natural language processing (NLP) and deep learning techniques, this project provides insights into the emotional tones (sentiments) of each song and generates new lyrics in the band's distinctive style. It combines exploratory data analysis (EDA) with interactive visualizations and builds a custom text generation model using TensorFlow's LSTM layers.
- Libraries: Pandas, Seaborn, Matplotlib, Plotly, TextBlob, TensorFlow, Keras.
- Machine Learning: LSTM-based model for sequential text generation.
- NLP: Tokenization, sentiment analysis, and GloVe embeddings for deeper context.