Data Science and Machine Learning: What does it take to succeed?

Logo
Presented by

Marty Klein,SVP of Defense and Intelligence, C3 AI; Joel Haas, Senior Solution Leader, C3 AI

About this talk

As opportunities for data science and machine learning flourish across the enterprise, there’s a growing friction between desires to build new systems and responsibilities to extract more value from legacy systems. With a survey of experiences across industries over the last decade – including Federal Government, Oil & Gas, Financial Services, and Precision Healthcare – we’ll explore what it takes to succeed with a modular open systems approach and how it can ease the friction.
Related topics:

More from this channel

Upcoming talks (0)
On-demand talks (104)
Subscribers (41539)
Join this channel to learn best practices and insights on how to: containerize existing apps for increased cost efficiency, deliver new cloud-native and process-driven apps using microservice architectures, take an agile approach to integrate APIs and data, and do it all in a culture of collaboration using DevOps best practices.