IBM® Decision Optimization for Watson Studio enables data science teams to capitalize on the power of prescriptive analytics and build solutions using a combination of techniques like machine learning and optimization. It is integrated with IBM® Watson Studio that combines optimization techniques with coding and non-coding tools, model management and deployment – as well as other data science capabilities. The solution evaluates millions of possibilities – balancing trade-offs and business constraints to find the best possible solution.

Deliver Business Results by Combining Optimization and Machine Learning

5 minute demo

In this video you can explore the benefits and use cases of combining machine learning techniques with decision optimization to deliver business results.

Develop and deploy machine learning and optimization models usingIBM Watson Studio and Watson Machine Learning

8 minute demo

This video introduces to IBM Watson Studio and Watson Machine Learning and demonstrates the capabilities of IBM value added tools that uses visual and guided approach to build and deploy predictive and prescriptive models

Solving a business problem with IBM SPSS Modeler and IBM Decision Optimization on IBM Cloud Pak for Data

10 minute demo

Within IBM Cloud Pak for Data, this video focuses on using IBM value added tools like SPSS Modeler and Decision Optimization models that uses visual and guided approach to build predictive and prescriptive models to solve retail promotion planning problem.

Deliver Optimal Business Decisions with IBM Data Science Experience

4 minute demo

Learn how IBM Decision Optimization for Data Science Experience provides the capabilities to combine optimization techniques with other data science capabilities to help deliver business impact.

Introduction to Decision Optimization for Watson Studio

4 minute demo

IBM Decision Optimization for Watson Studio allows you to run optimization models in Watson Studio, with a user-friendly environment in which you can combine optimization with data science.

IBM Decision Optimization in Action on Data Science Experience

8 minute demo

This video demonstrates the capabilities of IBM Decision Optimization for Data Science Experience that enables data science teams to capitalize on the power of prescriptive analytics and build solutions using a combination of techniques like machine learning and optimization.

IBM Decision Optimization Interface within Watson Studio - Python model

6 minute demo

The Decision Optimization Model Builder allows you to create prescriptive models within IBM Watson Studio. One can create several scenarios using different data sets and optimization models. This video shows the workflow on how to use model builder interface along with a Python.

Introduction to Decision Optimization for Data Science Experience

9 minute demo

Learn the value and capabilities of Decision Optimization and walk through a typical data science application to learn how it uses machine learning and optimization models. See how data scientists can easily combine both of these approaches to develop and deploy models.

Building Decision Optimization models using modeling assistant within Watson Studio

7 minute demo

Model Builder within Decision Optimization simplifies the process of creating optimization models. The modeling assistant uses natural language interactions to define goals and constraints for the model with no coding required.

Tour IBM Decision Optimization for Watson Studio: Create and deploy an optimization model

Build and deploy an optimization model like an expert with IBM® Decision Optimization for Watson Studio.

  • Create an optimization project and load a data set
  • Start to develop an optimization model and prepare the data set
  • Finish the development of the optimization model by using the modeling assistant
  • Solve the optimization model and review the results
  • Create a dashboard for the results
  • Experiment with different scenarios
  • Prepare the model for deployment

15-30 minute introduction