Cloudera Machine Learning Runtimes
Using PBJ Workbench
Requirements for using a PBJ Workbench
Dockerfile compatible with PBJ Workbench
PBJ Runtimes and Models
Example models with PBJ Runtimes
Using ML Runtimes add-ons
Adding Hadoop CLI to ML Runtime sessions
Adding Spark to ML Runtime Sessions
Turning off ML Runtimes add-ons
ML Runtimes NVIDIA GPU Edition
Testing ML Runtime GPU Setup
ML Runtimes NVIDIA RAPIDS Edition
Using Editors for ML Runtimes
Using JupyterLab with ML Runtimes
Installing a Jupyter extension
Installing a Jupyter kernel
Installing R Kernel in JupyterLab Runtimes of Cloudera AI
Using Conda Runtime
Installing additional ML Runtimes Packages
Restrictions for upgrading R and Python packages
Custom Runtime add-ons with Cloudera AI
ML Runtimes environment variables
ML Runtimes Environment Variables List
Accessing Environmental Variables from projects
Customized Runtimes
Creating customized ML Runtimes
Creating a Dockerfile for the custom Runtime Image
Metadata for custom ML Runtimes
Customizing the editor
Building the new Docker Image
Distributing the ML Runtime Image
Adding a new customized ML Runtime through the Runtime Catalog
Limitations to customized ML Runtime images
ML Runtimes Pre-installed Packages overview