This project leverages the power of natural language processing (NLP), data science, and machine learning to predict bankruptcy. By analyzing financial text data, sentiment analysis, and key economic indicators, the project aims to develop a robust model for early bankruptcy detection. Using Python libraries such as pandas, scikit-learn, and TensorFlow, this project integrates state-of-the-art machine learning techniques to forecast financial distress, offering valuable insights for investors and financial analysts.
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