End-to-End Machine Learning on Databricks Workshop

This 3 part workshop will walk you through a full model lifecycle, from processing input data to monitoring model performance over time.

Requirements

To access the latest ML features on databricks, including AutoML and pyspark.pandas, please use Databricks Runtime 10.0 ML or above.

Please clone this repo into your Databricks workspace using the Repos feature.

To create vizualizations and a dashboard to the one attached, make sure Databricks SQL is available for your workspace.

Thank you! Have a nice day

Name		Name	Last commit message	Last commit date
Latest commit History 13 Commits
01 - Data Preparation: Feature Engineering and AutoML.py		01 - Data Preparation: Feature Engineering and AutoML.py
02 - Data Exploration: Generated by AutoML.py		02 - Data Exploration: Generated by AutoML.py
03 - Best Trial Run: XGBoost training improvements.py		03 - Best Trial Run: XGBoost training improvements.py
End-to-End ML Workshop DB SQL Dashboard.pdf		End-to-End ML Workshop DB SQL Dashboard.pdf
End-to-End ML Workshop.dbdash		End-to-End ML Workshop.dbdash
README.md		README.md