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Be sure to check out his talk, “ ApacheKafka for Real-Time Machine Learning Without a DataLake ,” there! The combination of data streaming and machine learning (ML) enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the ApacheKafka ecosystem.
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It initially sources input time series data from Amazon Managed Streaming for ApacheKafka (Amazon MSK) using this live stream for model training. Post-training, the model continues to process incoming data points from the stream. It evaluates these points against the historical trends of the corresponding time series.
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The session participants will learn the theory behind compound sparsity, state-of-the-art techniques, and how to apply it in practice using the Neural Magic platform.
APIs Understanding how to interact with Application Programming Interfaces (APIs) to gather data from external sources. Data Streaming Learning about real-time data collection methods using tools like ApacheKafka and Amazon Kinesis. Once data is collected, it needs to be stored efficiently.
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