Machine Learning

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Enabling Java applications for low-latency use cases at massive scale with Azul Zing and GridGain

Even though Java applications dominate enterprise deployments, there is one area that is hard to conquer with a standard Java software stack. The area is represented by low-latency use cases that impose strict and non-negotiable rules obligating a selected software stack to process thousands of operations per second within sub-millisecond or microseconds boundaries for high percentiles. Think of credit cards authorization, payments processing, electronic trading as of typical examples of such applications.

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A Deep Learning Approach to Automatic Call Routing

Technological advancements are transforming customer experience, and businesses are beginning to benefit from Deep Learning innovations to automate call center routing to the most proper agent. This session will discuss how Deep Learning models can be run with Intel BigDL and Spark frameworks co-located on an in-memory computing platform to enhance the customer experience without the need for GPUs

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