Lakehouse for HLS: Patient readmission

00-patient-readmission-introduction

Introduction notebook, start here to implement your HLS Lakehouse.

01.1-DLT-patient-readmission-SQL

SQL DLT pipeline to ingest patient data & build clean tables.

02-Data-Governance-patient-readmission

Secure your tables, lineage, auditlog...

03-Data-Analysis-BI-Warehousing-patient-readmission

Feature engineering for credit decisioning

04.1-Feature-Engineering-patient-readmission

Prepare our features and labls

04.2-AutoML-patient-admission-risk

ML model training using AutoML

04.3-Batch-Scoring-patient-readmission

Batch scoring using the best model generated by AutoML

04.4-Model-Serving-patient-readmission

Create a real-time serving endpoint to enable live recommendation

04.5-Explainability-patient-readmission

Explain model outputs using Shapley values and personalize care

04.6-EXTRA-Feature-Store-ML-patient-readmission

Discover Databricks Feature Store benefits

05-Workflow-Orchestration-patient-readmission

Orchestrate all tasks in a job and schedule your data/model refresh

config

Setup schema and database name.