IBM has released a Beta version of Data Science Experience Desktop. You can read about the Beta on the Data Science Experience blog.
We are delighted to announce that this Beta includes four Decision Optimization Notebooks along with the DOcplex Python Modeling API and the community edition of our world-class CPLEX and CP Optimizer engines. The Notebooks are:
- Marketing Campaign using CPLEX: A bank wants to match offers with the customers most likely to take advantage of them.
- Oil Blending using CPLEX: An oil company seeks to maximize profits by producing the optimal mix of blends.
- Sports Scheduling using Constraint Programming: A sports league schedules games across two divisions.
- Golomb Ruler using Constraint Programming: Setting marks on a ruler such that no two pairs of marks are the same distance apart.
These Notebooks are also available from the Decision Optimization GitHub.