Organizations of all types and industries are dipping their toes into machine learning and artificial intelligence (AI). However, for most embarking on this transformational journey, the results remain to be seen. And for those who are already underway, scaling their results across their organizations is completely uncharted waters.
Machine Learning Operations (MLOps) allows organizations to alleviate many of the issues on the path to AI with ROI by providing a technological backbone for managing the machine learning lifecycle through automation and scalability.
In this latest Data Science Central podcast, The Foundation for Your AI Strategy: MLOps 101, you’ll find answers to the following questions:
What is MLOps? And why is it needed for organizations in my industry to become AI-driven?
What are the core elements of an MLOps infrastructure?
How can MLOps tools deliver trusted, scalable, and secure infrastructure for machine learning projects and use cases applicable to my industry?
How can MLOps help data science teams, business leaders, and IT professionals build a resilient and scalable foundation for their AI initiatives?
Ari Kaplan, Director of AI Evangelism and Strategy - DataRobot
Sean Welch, Host and Producer - Data Science Central