James Thomas: Unlike the early adopters, like Canvas and Blackboard who are just like, “Hey, let’s just get a system up that’s online.” We took the approach from the outset of, “Hey, we want a cohesive system that identifies these gaps. So how do we blend the offline learning with the online learning? And then how do we apply analytics to this?” Ginette: I’m Ginette, Curtis: and I’m Curtis, Ginette: and you are
I’m not going to explain what GPT-3 stands for, because it doesn’t matter. What matters is what it is and what it can do. And what it can do might surprise you. First of all, if you haven’t heard, GPT-3 is a machine learning model that can write text. Text that looks like a human wrote it. Almost out of thin air. It’s a cutting-edge, gigantic machine learning model that’s
Higher education institutions house lots of important data that bad actors can access and sell on the dark web, like students’ social security numbers, financial aid information, and national security research. Protecting this information should be a high priority for institutions, but it’s not always easy to apply best practices and enforce compliance measures. We chat with Brandon Sherman about these issues. Brandon Sherman: In the higher education sector, it’s
As VP of Data Science and Analytics at GE Aviation, Dinakar Deshmukh talks about how he, and the large team he is over, solve big problems internally and externally by splicing the power of data science with deep domain knowledge. 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
Telmo Silva created ClicData, an end-to-end SAAS BI platform, which as he describes, is the little guy coming up in the BI platform world. He talks about how his company was started, where it’s been, and where it’s going with cutting-edge R&D. He also offers additional thoughts on the role of data in the business world today. Telmo Silva: That’s the next thing that we’re trying to see, “well, if we
Keeping quality customers is the aim of nearly every healthy business. Cactus Raazi challenges the typical methods of doing this and suggests alternative data-focused pricing strategies in order for businesses to survive in the future. Cactus Raazi: When I started to write the book, my initial assumption was that there was going to be this price deflation or intense pure-price competition in homogenous goods. But I noticed that obviously hospitality is
Robin Purohit: There’s lots of signals in this data that indicates whether a person or a piece of content is highly valued by the user community. And that’s really invaluable when you are gonna combine that with that kind of domain focus on the IT industry. Ginette Methot: I’m Ginette, Curtis Seare: and I’m Curtis, Ginette: and you are listening to Data Crunch, Curtis: a podcast about how applied data
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, okay, if you have a new idea for business, search
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 the program. So a lot of the research I do
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 model had a really good time trying to predict that
