In our final piece in this series, we explore the scoping stage, where you define the project’s goals, assess feasibility, and determine the resources required to complete it successfully.

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

Read the key takeaways from IIA’s roundtable discussion on how companies approached AI in 2024 and their key challenges moving forward.

Read the key takeaways from IIA’s roundtable discussion on change management and AI.

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Discover how natural language processing is transforming the pharmaceutical sector and other industries with Ritu Saxena's expert insights.

Read the key takeaways from IIA’s roundtable discussion on building and leading AI teams.