FINCHAT - Financial Advice Chatbot

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Developed a state-of-the-art financial advice chatbot by optimizing Large Language Models (LLaMA) to provide personalized guidance.

The chatbot achieved a 20% improvement in advice accuracy by incorporating financial data integration and advanced terminology comprehension.

Leveraged BERT and Named Entity Recognition (NER) to enhance response quality by 30% through sentiment-aware insights. The solution was implemented as an end-to-end application using Streamlit, offering real-time financial guidance with a modular and interactive interface.