IBM Decision Optimization provides best-in-class prescriptive analytics capabilities in Watson Studio.
Decision Optimization runtimes allow data science teams to easily combine optimization within a unified platform for unique approaches to complex business decision-making problems. Teams can build, test, and tune Decision Optimization models using Jupyter notebooks in Watson Studio.
New, reduced base rate
We are pleased to announce that we have reduced the base rate for using Decision Optimization in Watson Studio from 20 to 5 capacity unit hours. Below is the new CUH table, to be effective from May 1, 2020:
We have multiple notebooks samples available for Decision Optimization modeling in our gallery to start building, testing, and tuning Decision Optimization models in a matter of moments: