Turning My AI Banking Risk Project Into a Live Interactive Dashboard
📰 Medium · Data Science
Turn an AI banking risk project into a live interactive dashboard using Streamlit for real-time analytics and predictions
Action Steps
- Build a synthetic banking ML project using Python and relevant libraries
- Configure a Streamlit app to integrate with the ML project
- Test the app with sample data to ensure functionality
- Deploy the app to a cloud platform for live interaction
- Apply churn prediction and anomaly detection models to the dashboard for real-time insights
Who Needs to Know This
Data scientists and analysts can benefit from this tutorial to create interactive dashboards for stakeholders, while product managers can use it to inform product decisions
Key Insight
💡 Streamlit can be used to create interactive dashboards for AI projects, enabling real-time analytics and predictions
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️ Turn your AI banking risk project into a live dashboard with Streamlit!
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