Description
Many models important to inferential statistics and machine learning use some form of optimization under the hood. For example, least squares regression and support vector machines are both implemented as simple optimization models. With the right tools in your hands, optimization can do so much more! This talk shows how to implement familiar statistical models directly using optimization solvers.
Key take-aways
- Many statistical techniques are based on some sort of optimization.
- Optimization has lots of uses, such as solving decision models.
- Learning to structure problems you already know for optimization solvers is a great way to understand them!