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Managing Engines in Cloudera Machine Learning
Managing Engines
Managing Engine Profiles
Configuring the Engine Environment
Installing Additional Packages
Using Conda to Manage Dependencies
Engine Environment Variables
Engine Environment Variables
Accessing Environmental Variables from Projects
Customized Engine Images
Creating a Customized Engine Image
Create a Dockerfile for the Custom Image
Build the New Docker Image
Distribute the Image
Whitelist the Image in Cloudera Machine Learning
Limitations
End-to-End Example: MeCab
Pre-Installed Packages in Engines
Base Engine 13-cml-2020.08-1
Base Engine 12-cml-2020.06-2
Base Engine 11-cml1.4
Base Engine 10-cml1.3
Base Engine 9-cml1.2
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