Labels and Where To Find Them

All good things must come to an end, including this podcast. This is the last episode we plan to release, and it doesn’t cover data science—it’s mostly reminiscing, thanking our wonderful audience (that’s you!), and marveling at how this thing that started out as a side project g ...  Show more

The data science and artificial intelligence community has made amazing strides in the past few years to algorithmically automate portions of the healthcare process. This episode looks at two computer vision algorithms, one that diagnoses diabetic retinopathy and another that cla ...  Show more

Labels are everywhere. We want to belong to certain communities and groups. We want to belong, period. We also want to feel understood, both by others and by ourselves. But what are some downsides of seeking out labels? 

Theo is in the interviewer’s chair for this episode as Frank Liu from Zilliz joins the show to talk about how AI and machine learning are making it possible for developers to understand and extract more value from unstructured data such as text, audio, images, video, and more. Tr ...  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 ...

<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 ...