12/17 Webinar: Adding Optimization to Your Data Science Analytics Toolkit
Upcoming ODSC Webinar on December 17, 1pm-2pm EST
Mathematical optimization, specifically Mixed Integer Programming (MIP), is a technology that is used to solve a large variety of problems within multiple industries, including supply chain planning, electrical power generation and distribution, computational finance, sports scheduling, and many more. This powerful technology is complementary to Machine Learning and should be a part of every data scientist’s analytics toolbox.
In this webinar, you will learn:
- The basics of optimization and MIP
- How to identify optimization problems within your organization
- When to use MIP vs Artificial Intelligence (AI) when developing a prescriptive analytics solution for your business problem
- How MIP can be used as a complementary technique to Machine Learning
We will present real-world examples of Machine Learning and optimization in action, illustrating the value it can bring to your organization. We will also provide you with the next steps on how to get started with optimization as well as available resources.
Presenting this webinar are Dr. Gwyneth Butera (Sr. Support Engineer, Gurobi Optimization), and Dr. Russell Halper (Principal, End-to-End Analytics).
Dr. Butera has over 20 years of optimization software experience. Prior to joining Gurobi Optimization, she worked as a software engineer for IBM ILOG CPLEX Optimization Studio. More recently, she completed an immersive course in Data Science. She has her PhD in Computational and Applied Mathematics from Rice University.
Dr. Halper holds a PhD in Applied Mathematics from the University of Maryland. Russell is passionate about developing actionable, pragmatic analytics that align closely with business processes to generate world-class results. He has devoted his career to developing cutting-edge analytics solutions to problems in supply chain, manufacturing, and marketing.
