Setup:
Admin->Engine
Engine Profile: 2 CPU / 8GB Memory (Add)
Start a Python3 Session (at least 8gb memory) and run utils/setup.py
This will install all requirements for the code below.
Alternatively you can create a custom docker engine using the utils/Dockerfile.
For the CML trials contact Cloudera for a link to the engine image.
Create a new engine as a CML admin with the following editors
-RStudio /usr/sbin/rstudio-server start
-Jupyter Notebook /usr/local/bin/jupyter-notebook --no-browser --ip=127.0.0.1 --port=${CDSW_APP_PORT} --NotebookApp.token= --NotebookApp.allow_remote_access=True --log-level=ERROR
Demos
0. Setup CDP Environment and CML Workspace
- Batch and online scoring of images with TensorFlow on spark
- Experiment Tracking and NLP model training for sentiment analysis of Twitter feeds
- Rstudio analysis of airline data from CDW or HMS/external tables and iDbroker