ML Model Deployment and Scoring on the Edge with Automatic ML & DF / Flink2Kafka
6:00 PM (EDT)
Machine Learning Model Deployment and Scoring on the Edge with Automatic Machine Learning and Data Flow
Deploying Machine Learning models to the edge can present significant ML/IoT challenges centered around the need for low latency and accurate scoring on minimal resource environments. H2O.ai's Driverless AI AutoML and Cloudera Data Flow work nicely together to solve this challenge. Driverless AI automates the building of accurate Machine Learning models, which are deployed as light footprint and low latency Java or C++ artifacts, also known as a MOJO (Model Optimized). And Cloudera Data Flow leverage Apache NiFi that offers an innovative data flow framework to host MOJOs to make predictions on data moving on the edge.
Join us for an interesting talk and learn how to push Driverless AI Machine Learning models to the edge using Cloudera Data Flow.
We will be using a public UCI ML Hydraulic Systems Condition Monitoring dataset to build a Driverless AI model, download it as a MOJO scoring pipeline and push it to the edge using Cloudera Flow Management (Apache NiFi). This meetup will be driven around this scenario from slides to demo. We will also show how to do ML edge inference with Cloudera Edge Management (Apache MiNiFi C++). In this use case, ML edge inference can be used for Hydraulic System Predictive Maintenance for monitoring the Hydraulic cooling condition, valve condition, pump leakage, accumulator, and stability.
James Medel (H2O.ai - Technical Community Maker)
Greg Keys (H2O.ai - Solution Engineer)
Tim Spann (Cloudera)
FLaNK Stack Integration with MiNiFi, NiFi, Kafka and Flink.
7:00 PM (EDT)
Kafka 2 Flink - An Apache Love Story
This project has heavily inspired by two existing efforts from Data In Motion's FLaNK Stack and Data Artisan's blog on stateful streaming applications. The goal of this project is to provide insight into connecting an Apache Flink applications to Apache Kafka.
Ian R Brooks PhD | Senior Solutions Engineer & Data | Cloudera
Web Conference information to be provided.