Summary
The project uses AI to generate Shakespearean-style poetry by training an LSTM-based model. It combines creativity and technology, producing text with high thematic and structural accuracy.
Project overview
Overview:
This project explores the use of AI in creative text generation by developing a model that produces Shakespearean-style poetry. By leveraging LSTM-based models and advanced NLP techniques, it highlights the potential of generative AI for creative applications.
Key Highlights:
- Tools Used: Python, Machine Learning, Deep Learning, and Generative AI.
- Objective: To create an AI system capable of generating domain-specific text with thematic and structural coherence.
- Process: Designed an LSTM-based text generator model trained on a dataset specific to Shakespearean poetry.
- Accuracy: Achieved 80% accuracy in producing text that aligns with the thematic style and structure of the dataset.
- Impact: Demonstrated how sequence modeling can enable creative AI applications in literature and beyond.
Summary:
This project showcases the role of generative AI in pushing the boundaries of creativity, offering insights into how machines can assist in artistic endeavors.
