Uncertainty and volatility are compelling business leaders to apply data science and AI innovation to a broader set of organizational functions. How do you predict customer behaviors when models are becoming outdated very quickly? Are you challenged with tackling staff productivity and logistics when balancing remote and physical work? With an integrated approach to AI, organizations can increase predictability, optimize operations and drive resiliency even when market conditions are rapidly changing — from customer experience and workforce optimization to inventory optimization and risk management.
Register now and learn the latest on data science and AI best practices to help chart your path to recovery and growth.
December 8, Part 3: What's new with data science - advancements in Watson Studio on IBM Cloud Pak for Data,
The third session will focus on the latest innovation in Watson Studio, including:
- Automated AI lifecycles and unified experience
- Multicloud ModelOps deployment from edge to hybrid clouds
- Productivity and value accelerators with decision optimization and SPSS Modeler
- Accelerated deep learning with a multitenant architecture
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Presenters:
Thomas Schaeck
Distinguished Engineer, Watson Studio, IBM Data and AI
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Yin Chen
Offering Manager, Watson Studio, AutoAI and deep learning, IBM Data and AI
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Kelvin Liu
Senior Technical Offering Manager, Watson Machine Learning Accelerator, IBM Data and AI
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Julianna DeLua
SME, data science and AI, IBM Cloud Pak for Data, IBM Data and AI
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