Applied Machine Learning in Real-Time with Distributed, Scalable, In-Memory Technology
Watch NowBrought to you by: Intel and Hazelcast
Machine learning (ML) brings exciting new opportunities, but applying the technology in production workloads has been cumbersome, time-consuming, and error-prone. In parallel, data generation patterns have evolved, generating streams of discrete events that require high-speed processing at extremely low response latencies. Enabling these capabilities requires a scalable application of high-performance stream processing, distributed computing of ML technology, and dynamically scalable hardware resources.
In this webinar, learn how the Hazelcast In-Memory Computing Platform enables the application of ML (Java, Python, C++) algorithms on real-time data streams with a distributed, cooperative, low-latency architecture.ย Additionally, we’ll examine how Intelโs next generation processors coupled with Intel Optane memory capabilities are expanding the possibilities for in-memory platform applications.
