overview
This solution architecture helps you understand how to build a near-real time Fraud Detection App that ingests credit card transactions data, carry Feature Engineering, build a Classification model object using Snowflake ML within Snowflake Notebooks and carry ongoing detection in a Streamlit App. of the use cases are described below.
- Data Ingestion and carry Data exploration.
- Perform Feature Engineering and store the generated features in Snowflake Feature Store
- Leverage Snowflake ML Function and build a Binary classification model
- Carry ongoing inference using a Streamlit App with the trained model.
