Autorecovery: Imputation in a Knowledge Graph | Austin

About this event

Overview: At this monthly event series, we host thought-leaders from the Austin data community to discuss the possibilities that data brings to life. They’ll cover how today’s wealth of data drives business and product decisions across a range of industries, and share their visions for the future.

This month, we're excited to host Hypergiant's Lead Data Scientist, Drew Lipman.

Data Scientists spend an enormous amount of time preprocessing, cleaning, and feature engineering data. This is a daily part of Data Science and Artificial Intelligence. Despite that, there is surprisingly little theoretical research into this process. Simple problems like imputing missing data, which is well known for SQL databases or tables of data, becomes challenging when the missing data is from a Graph Database, or some other knowledge structure. In this talk, Drew will discuss early exploration for imputation techniques for data in a Knowledge Graph, the parallels to existing classical imputation methods, and the difficulties in automating this process.