Decision Optimization in Python Notebooks for Watson Studio

1 min read

Decision Optimization environments with Python are Generally Available to users of Watson Studio Notebooks.

IBM Decision Optimization delivers prescriptive analytics capabilities to enable organizations to make better decisions and achieve business goals. With Decision Optimization, IBM Watson Studio users benefit from a combination of data science features and prescriptive analytics so they can solve the toughest problems that might require optimization, such as shelf-space allocation, marketing campaigns, or maintenance scheduling. 

One of the most powerful and flexible ways to build Decision Optimization models is with Python. Over the past few months, a Beta environment with Decision Optimization and Python was available to users of Watson Studio Notebooks. 

Following a successful beta roll-out, support for Decision Optimization and Python is now generally available for all IBM Watson Studio users. 

Here are the dates you need to know

  • Decision Optimization Environment Beta Release Date: December 7, 2018
  • Decision Optimization Environment Release Date: July 26, 2019

Importantly, you might need to act to update your notebooks that currently rely on the Decision Optimization Beta environment with Python 3.5. We made that announcement here for all Python 3.5 environments. 

If you do not act, you will simply be prompted to select the new environment when you edit an existing notebook with the Python 3.5-backed environment. The older Beta Decision Optimization environments on Python 3.5 will be removed on July 26, 2019, as a part of the release. 

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