In this week's episode of Making Data Simple, we are joined by guest John DeNero, who is a professor at UC Berkeley. John specializes in teaching artificial intelligence, and he won a distinguished teaching award in 2018. Host Al Martin and John discuss methods of teaching AI, the state of the
In part one of the Capitalogix data science story, I focused on their strategic need for a data platform that supports speed, data variety and custom-built algorithms to find advantages for their business. A key success driver: they worked to make life better for the people on the front lines of
Financial services organizations face considerable challenges today. From regulatory changes to globalization to shifting customer expectations, the urgent need to re-engineer outdated systems to better manage vast amount of data can apply additional pressure. Organizations must deal with the
There is no AI without data. That’s why we’ve put together a prescriptive set of five steps we call the ladder to AI to help our enterprise clients get their data ready. The journey of the AI ladder starts with collecting the data you need to build models, followed by organizing your data so you
Guy Taylor, head of data and data driven intelligence at Nedbank, joins the podcast. He and host Al Martin discuss the state of the banking industry, machine learning practices -- and why you should add a South African safari to your bucket list. Suit up for an incredibly engaging conversation.
Prescriptive analytics helps identify the best course of action that can enable businesses to achieve organizational goals. Although figuring out what you should do is a crucial aspect of business, the value of prescriptive analytics is often missed. There is still an inclination to “go with the
In part 1 of a part 2 series, host Al Martin peels the onion with Janine Sneed. Bold, energetic, passionate, and results-driven, Janine serves in two distinct roles at IBM: Chief Digital Officer and VP of Customer Success for IBM Data and AI. This week, Janine and Al look at product management,
IBM anticipated barriers to scaling enterprise AI. We developed a platform to help clients operationalize AI faster while infusing trust and transparency with IBM Cloud Private for Data and the add-on Watson OpenScale.