talk-data.com talk-data.com

M

Speaker

Mark Palmer

2

talks

author

Filter by Event / Source

Talks & appearances

2 activities · Newest first

Search activities →
The Future of Data Visualization—Panel Outlier 2025

The Future of Data Visualization—Panel Outlier 2025

🌟Outlier is a one-of-a-kind data visualization conference hosted by the Data Visualization Society. Outlier brings together all corners of the data visualization community, from artists to business intelligence developers, working in various tech stacks and media. Attendees stretch their creativity and learn from practitioners who they may not otherwise connect with. Learn more on the Outlier website: https://www.outlierconf.com/


📈About the Data Visualization Society: The Data Visualization Society was founded to serve as a professional home for those working across the discipline. Our mission is to connect data visualizers across tech stacks, subject areas, and experience. Advance your skills and grow your network by joining our community: https://www.datavisualizationsociety.org/

Ten Things to Know About ModelOps

The past few years have seen significant developments in data science, AI, machine learning, and advanced analytics. But the wider adoption of these technologies has also brought greater cost, risk, regulation, and demands on organizational processes, tasks, and teams. This report explains how ModelOps can provide both technical and operational solutions to these problems. Thomas Hill, Mark Palmer, and Larry Derany summarize important considerations, caveats, choices, and best practices to help you be successful with operationalizing AI/ML and analytics in general. Whether your organization is already working with teams on AI and ML, or just getting started, this report presents ten important dimensions of analytic practice and ModelOps that are not widely discussed, or perhaps even known. In part, this report examines: Why ModelOps is the enterprise "operating system" for AI/ML algorithms How to build your organization's IP secret sauce through repeatable processing steps How to anticipate risks rather than react to damage done How ModelOps can help you deliver the many algorithms and model formats available How to plan for success and monitor for value, not just accuracy Why AI will be soon be regulated and how ModelOps helps ensure compliance