Presented by Vijay Pappu, Senior ML Engineering Manager, Personalization Lead at Peloton, this talk focuses on any ML systems that rely on a feedback loop for improvement. How do we measure the efficacy of an ML system?
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Industry Perspectives
How to Evaluate Your Data Footprint
In this special guest feature, Ahson Ahmad, Chief Product and Customer Officer, Ripcord, presents an interesting take on ‘Data Heat’ which is how it’s possible to help customers determine which data to delete, and which data to store.
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insideBIGDATA Guide to Optimized Storage for AI and Deep Learning Workloads
This new technology guide from DDN shows how optimized storage has a unique opportunity to become much more than a siloed repository for the deluge of data constantly generated in today’s hyper-connected world, but rather a platform that shares and delivers data to create competitive business value. The intended audience for this important new technology guide includes enterprise thought leaders (CIOs, director level IT, etc.), along with data scientists and data engineers who are a seeking guidance in terms of infrastructure for AI and DL in terms of specialized hardware. The emphasis of the guide is “real world” applications, workloads, and present day challenges.
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