In this contributed article, Naomi Beckett, Senior Data Scientist at SparkBeyond, discusses the importantance of error analysis in predictive modeling and how to establish a method for determining when enough is enough.
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Industry Perspectives
Embracing and Leveraging the Data-Driven Pressure in Industry 4.0
In this special guest feature, John Joseph, CEO & Co-founder of Datanomix, explores why real-time actionable manufacturing data is needed for the entire organization to determine the true quote to cost value, how leveraging data analytics that can be learned, consumed, and responded to in seconds, not minutes or hours will set factories ahead – especially post COVID-19, and how to leverage data to make smarter business decisions and better quote to cash estimates.
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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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