Databricks for ML Training: A 1-Hour Quickstart
Get hands-on with Databricks to build and manage ML training pipelines in this fast-paced, practical introduction.
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Databricks Lakehouse and MLflow Fundamentals
Unit 1: Databricks Lakehouse Platform
Intro to Lakehouse
Delta Lake Deep Dive
Unit 2: Databricks Workspace Setup
Workspace Setup
Cluster Configuration
Unit 3: Databricks Notebooks and PySpark
Notebook Basics
PySpark Intro
Data Exploration
Unit 4: MLflow Experiment Tracking
MLflow Intro
Tracking Experiments
Autologging
Accelerated Model Development and Deployment
Unit 1: Databricks Autologging and AutoML
Intro to Autologging
Autologging in Action
Intro to AutoML
Running AutoML
AutoML Results
Unit 2: Scaling ML Pipelines and Model Management
MLflow Model Registry
Registering Models
Model Deployment
Model Monitoring
Accessing Data