Presented by
Cal Foshee, IBM; Eric Gamble, IBM; Erik Smith, Dell Technologies
From Data to Decisions: Understanding How AI Models Learn
About this talk
Join us for an insightful webinar and demonstration as we explore the foundational process of training machine learning models, with a special focus on computer vision applications. This session will guide participants through the essential stages of model development—from data preparation to algorithm selection—highlighting how these steps influence performance and accuracy.
Through practical demonstrations and conceptual discussions, attendees will gain a deeper understanding of how vision models are built and validated, and how these techniques can be extended to broader predictive analytics. We’ll also examine common challenges and share strategies to overcome them, emphasizing the value of simplicity, modular design, and thoughtful evaluation.
Key Takeaways:
• Core steps in the model training lifecycle
• Why data quality is critical to success
• Understanding inferencing and metrics for model validation
• Shifting from engineering mindset to modeling intuition
• Avoiding common pitfalls in training workflows
• Embracing parsimony and modularity in design
• Using checkpoints to monitor and refine progress
Data Center Management
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Best practices for achieving an efficient data center
With today’s pressures on lowering our carbon footprint and cost constraints within organizations, IT departments are increasingly in the front line to formulate and enact an IT strategy that greatly improves energy efficiency and the overall performance of data centers.
This channel will cover the strategic issues on ‘going green’ as well as practical tips and techniques for busy IT professionals to manage their data centers. Channel discussion topics will include:
- Data center efficiency, monitoring and infrastructure management;
- Data center design, facilities management and convergence;
- Cooling technologies and thermal management
And much more