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Nature Language Processing/ML on an IoT Edge Device Using MiNiFi
Recently, I had an opportunity to dive incredibly deep with MiNiFi to deploy business logic on an edge device. The task was to identify a pattern that could be used to have an edge device execute or call an ML model. Many edge devices do not have enough compute to constantly run ML models; therefore, leveraging Model as a Service or an end point to the model execution becomes super rich within this domain challenge. The example/demo described in this article will deploy a MiNiFi (an edge agent) to receive text from anyone (high interactive demo), have it call a model service ( i.e. Cloudera Data Science WorkBench) to perform text sentiment (positive, negative, neutral), and finally have it forward the text and sentiment to NiFi. Once NiFi receives the data, publishing to downstream to Spark, DataLake, S3, ADLS, Ozne, etc. becomes incredibly simple.
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