Release 0.10

• Update launch_dss to print suitable port connection message depending on platform
• Disabled Jupyter notebook password prompting
• Removed sample programs to separate directory
• Simplified process to download images and start containers
• Bootstrap scripts available to automatically configure gpu and non-gpu ec2 instances to support data science_containers
• Published following docker images to dockerhub.com

Docker Image	Description
dsimages/rstudio	Rstudio Server Community Edition
dsimages/h2oai	h2o Flow Server

Release 0.9

Added following packages to jpynb image:

• h2o
• lightgbm
• xgboost

Fixed permission issue between MacOS and Linux when running docker containers

Published several of the docker images to dockerhub.com

Docker Image	Description
dsimages/jpynb	Anaconda Python with Jupyter Notebook additional data science packages
dsimages/pyspnb	Anaconda Python with Jupyter Notebook and Apache Spark (stand-alone)
dsimages/tfcpu	TensorFlow with Python 3 and Jupyter Notebook
dsimages/tfgpu	TensorFlow with Python 3 and Jupyter Notebook with CUDA libraries. Designed to run on AWS ec2 gpu-enabled instances.

Release 0.8

Added h2o stack

Release 0.7

• Standardized location for source code directory (my_workarea)
• Container with Anaconda Python and Tensorflow (cpu-only)

Release 0.6

Removed Python 2.7 kernel from jpynb service

Separated starting service from launching web browser. Typical command sequence:
start_dss <service> <directory>
launch_dss <service>

Re-enabled password for Jupyter notebooks

Release 0.5

Added Anaconda Python with stand-alone Spark

Release 0.4

Support running with Kubernetes on the MacOS

Release 0.3

Code clean-up

Release 0.2

Provided several bash scripts to facilitate starting docker containers.

Release 0.1

Initial release, working versions for Anaconda Python