[MINI] Data Provenance

The data we collect about ourselves can tell us a lot—but only if the technology collecting it actually fits into our lives. Daniel Epstein explores personal informatics, from fitness trackers and food journals to baby tracking and AI, and explains why abandoning a tracking tool ...  Show more

In the final episode of our Recommender Systems season, we explore the growing questions of trust, manipulation, privacy, fairness, sustainability, and user control. From fake reviews and shilling attacks to explainable recommendations and user-selected algorithms, we look at wha ...  Show more

In episode eleven of season five, we dig in to just what a data trust actually is, take a look at citation trends and other places <a href="http://proceedings.mlr.pr ...

<div class="wp-block-jetpack-markdown"><h2>Summary</h2>

Data is useless if it isn’t being used, and you can’t use it if you don’t know where it is. Data catalogs were the first solution to this problem, but they are only helpful if you know what you are look ...

In this episode of the SuperDataScience Podcast, I chat with Aspiring Data Scientist Nicholas Cepeda. You will be able to discover the many different pathways in Data Science, learn R from a SQL background and hear about SAS Enterprise Miner. If you enjoyed this episode, check o ...  Show more

<div class="wp-block-jetpack-markdown"><h2>Summary</h2>

The most important gauge of success for a data platform is the level of trust in the accuracy of the information that it provides. In order to build and maintain that trust it is necessary to invest in defining, monitori ...