As the first Mexican woman to get a PhD from Stanford, Debbie Berebichez has experienced what it takes to challenge norms and boundaries. She speaks about her personal experience overcoming cultural norms regarding women in STEM and her professional experience training company culture in data science. Debbie Berebichez: It’s very important to encourage people to be evidence based. To see,…
Matthew Battifarano has always been interested in mobility and transportation. He talks to his intrigue with traffic equilibrium, which includes autonomous vehicles, ride hailing, bike sharing, etc.; what shaped it; and what lead him to his PhD at the Mobility Data Analytics Center at Carnegie Mellon University. Matthew Battifarano: This is something I’d never heard of before, before I started in…
Ian Cassidy: When you did a PCA, a principal component analysis, like, it was like beautiful. There was, like, a red circle in the middle of, you know, the blue on purchase, you know, data points. And there were the red purchase ones and they were all clustered together. It was, it was really interesting. And like the, the machine learning…
Does it feel like your stakeholders aren’t open to adopting your team’s algorithms? Ylan Kazi shares his experience on how to conquer this type of problem. Ylan Kazi: And that is very important. But I think what we find, especially in larger organizations and in trying to implement these things across an enterprise, is that the relationships and the communication are really…
Hiring top tech talent is hard, especially when these people are in high demand. So how can you build your tech team? HR and hiring experts Laura and Theo talk about their process. Laura Ianuly: I think the most important thing, the best advice I could give a hiring manager is making sure that they understand what they’re looking for. They’ve…
Many companies are sitting on data assets that could be revenue streams for them, without knowing it. Matt Staudt of VDC discusses making latent data profitable. Ginette: I’m Ginette, Curtis: and I’m Curtis, Ginette: and you are listening to Data Crunch, Curtis: a podcast about how applied data science, machine learning, and artificial intelligence are changing the world. Ginette: Data Crunch is produced by the…
What does it look like to shape a social media platform? Max Sklar can speak to that having worked on machine learning at one for nearly its entire existence. In today’s episode, he talks about what’s worked and what hasn’t at Foursquare. Max Sklar: So Foursquare’s a very positive platform, but the Japanese language is off the charts. You have 97%…
Distribution in Tableau In the business world, you’ll hear averages get referenced all the time. “What’s the average number of admissions per day?” or “What’s the average profit per month?” or “How are we trending compared to our average?” Those are all fine – even vital – things to know. But they obscure insights hidden in the data. It assumes…
The Data pane contains a few fields that are not part of your data, two of which are Tableau Measure Names and Tableau Measure Values. The Measure Values field always appears at the bottom of the Tableau Measures area of the Data pane and contains all the measures of your data collected into one field. The Tableau Measure Names field always appears at…
Curious about graph databases? Matthias Broecheler from DataStax talks with us about looking at the world through a graph lens and using it to solve real world problems. Ginette: I’m Ginette, Curtis: and I’m Curtis, Ginette: and you are listening to Data Crunch, Curtis: a podcast about how applied data science, machine learning, and artificial intelligence are changing the world. Ginette: Data crunch is produced…