00-FSI-fraud-detection-introduction-lakehouse
Start here to explore the Lakehouse.
01-Data-ingestion
01.1-DLT-fraud-detection-SQL
SQL DLT pipeline to ingest data & build clean tables.
02-Data-governance
02-UC-data-governance-ACL-fsi-fraud
Secure your tables, lineage, auditlog...
03-BI-data-warehousing
03-BI-Datawarehousing-fraud
Run interactive queries on top of your data
04-Data-Science-ML
04.1-AutoML-FSI-fraud
Leverage Databricks AutoML to create a Fraud model in a few clicks
04.2-automl-generated-notebook-fraud
Explore the best Fraud model generated by AutoML and deploy it in production.
04.3-Model-serving-realtime-inference-fraud
Once your model is deployed, run low latency inferences.
04.4-Upgrade-to-imbalance-and-xgboost-model-fraud
Improve AutoML model to handle imbalanced data.
04.5-AB-testing-model-serving-fraud
Deploy the new model comparing its performance with the previous one.
05-Generative-AI
05.1-AI-Functions-Creation
Utilize Databricks AI functions to generate automated fraud report generation.
05.2-Agent-Creation-Guide
Define an AI agent with the functions you defined in notebook 04.1
06-Workflow-orchestration
06-Workflow-orchestration-fsi-fraud
Orchestrate all tasks in a job and schedule your data/model refresh
config
Setup schema and database name.