
Machine Learning Lifecycle, Part 2: Selecting and Training Models
In Part 2 of “Machine Learning Lifecycle,” the author explores selecting and training models, with data-centric model development at its core.
In Part 2 of “Machine Learning Lifecycle,” the author explores selecting and training models, with data-centric model development at its core.
In this multi-part series, the author begins at the final stage of the machine learning lifecycle: deployment. Explore key challenges, deployment patterns, and degrees of automation.
IIA clients want to know more about agentic AI. This article elaborates on the multi-agent system and how it operates
IIA Roundtable Peer Insights
Read the key takeaways from IIA’s roundtable discussion on how companies approached AI in 2024 and their key challenges moving forward.
IIA Roundtable Peer Insights
Read the key takeaways from IIA’s roundtable discussion on change management and AI.
IIA Roundtable Peer Insights
Read the key takeaways from IIA’s roundtable discussion on balancing AI, automation, and human-centric work.
Breakthrough Conversations
Discover how natural language processing is transforming the pharmaceutical sector and other industries with Ritu Saxena's expert insights.
RAN Roundtable Peer Insights
Read the key takeaways from IIA’s roundtable discussion on building and leading AI teams.
Accelerating Your Data Innovation Journey in Healthcare
In our latest installment on data innovation in healthcare, the authors discuss practical applications of intelligent automation and provide a framework for how to assess your readiness.