LL-ML shared you an appDevelop a Python application that processes uploaded .csv files containing lead data with multiple columns. The application should: 1. Analyze the lead data using NLP and AI techniques to categorize leads by type and identify target groups based on the content of the lead names and other relevant fields. 2. Create a dynamic database to store all product and lead list information efficiently. The database should be designed to handle queries related to lead types and target groups effectively. 3. Incorporate an AI chatbot that interacts with the user to gather information about the products and helps in creating a tailored database structure for storing product and lead data. 4. Implement a dashboard interface using a suitable Python library like Dash or Streamlit, which displays available lead types, potential target groups, and provides recommendations on which targets to approach first for specific products. 5. Enable cold email marketing campaigns with a feature that allows the user to initiate campaigns directly from the UI for selected lead sub-lists based on the analysis done by the app.
