A Grammar of Analytics - Model Agnostic Interpretability for Machine Learning

Building Statistical / Machine Learning models is an effective way for understanding the relationship among the variables. But understanding of the models is another story. In the world of data science, most of the times each type of the models (e.g. Linear Regression, Random Forest, etc.) produces the result in its own way. This means that you need to learn how to interpret the result for each model type.

With Exploratory, we provide a consistent framework called 'Grammar of Analytics', which produces a same set of information along with visualization that help you interpret the model intuitively for all the Statistical / Machine Learning models. This means, once you learn the basics of the Grammar of Analytics, you can understand any models in the same way.

In this seminar, Kan introduces the Grammar of Analytics and show you how you can understand the model outputs with Exploratory.

Agenda:

• Prediction Models
• A Grammar of Analytics
• Correlation & Causation
• Multivariate Analysis
• Statistical Models vs. Machine Learning Models

Past Seminars

You can check other past seminars on this page.

For the upcoming seminars, check out our Exploratory Online Seminar page!