Making Data Simple host Al Martin looks back on his top 5 favorite clips from episodes published in 2018. These conversations range from explaining the importance of data visualization, to discussing the differences between A.I. and deep learning. Thanks to all of our listeners for an incredible
On this week's episode of Making Data Simple, we talk about the future of AI, machine learning, and Watson with Steven Astorino, VP of development, hybrid cloud, z Analytics and IBM Canada lab director.
How do baseball scouts use machine learning and AI to predict player performance? Ari Kaplan, Principal at Aginity, and David Kearns, Offering Manager, IBM Analytics Ecosystem, join us to talk about the recent merge of H20.ai and IBM. They also discuss how baseball decisions are made using
On this week's episode, John J Thomas, Distinguished Engineer and Director for IBM Analytics, and Steve Moore, Senior Content Designer and Story Strategist, join us to talk about data science and how your business can best weave the skills of a data scientist into their decisions. Learn how to
On this episode of Making Data Simple, we change gears as our guest Daniel (Danny) Hernandez, VP Analytics Offering Management, interviews host, Albert V Martin, VP of Hybrid Platform Development and Client Success. Learn how to create a long-lasting relationship with clients, the difference
On the second episode of Data Decoded, Seth Dobrin, VP & CDO of IBM Analytics discusses his role as a Chief Data Officer at IBM and the latest IBM Analytics announcements from Think 2018, from IBM Cloud Private for Data to launch of the Data Science Elite Team.
Moving data often impacts system performance, so how do you move large volumes of data safely and securely? The importance of data movement is even more critical when you consider moving data from ground to Cloud. Joe Bostian, z Systems Data Science Architect, IBM Analytics, and Mythili
In this week's episode of Making Data Simple, Al Martin and Adam Storm, IBM senior technical staff member and master inventor, next-generation HTAP architect, sit down to talk about fast data. Adam also covers the pros and cons of different information architectures and the software you can use to
What is driving change in the world of data? In his keynote from the Big Data Summit KC 2017, our Making Data Simple podcast host and IBM Analytics VP Al Martin addresses disruption, the data maturity model and the five areas business must get right to succeed in the era of cognitive computing.
J White Bear is a data scientist and software engineer at IBM. In this podcast, White Bear discusses simultaneous localization and mapping, an ongoing research area in robotics for autonomous vehicles and well-recognized as a nontrivial problem space in both industry and research.
Seth Dobrin is vice president and CDO, IBM Analytics, platform development, at IBM. In this podcast, Dobrin shares experiences using Apache Spark for data science transformation and some thoughts on a larger vision for data science transformation at scale.
Holden Karau is a software engineer at IBM, an active open source contributor and coauthor of Learning Spark (O'Reilly Media, February 2015) and the soon to be released High Performance Spark (O'Reilly Media, March 2017). In this podcast, Karau examines how to effectively search logs from Apache
Nick Pentreath is a principal engineer at IBM, a member of the Apache Spark project management committee (PMC) and author of Machine Learning with Spark (Packt Publishing, December 2014). In this podcast, Pentreath covers the basics of feature hashing and how to use it for all feature types in