Efficient Integration of Kubeflow Tools - ISS Data Case Study on Anomaly Detection

Explore a comprehensive case study on anomaly detection using International Space Station (ISS) telemetry data, demonstrating the efficient integration of Kubeflow tools in an end-to-end workflow. Learn how to orchestrate multiple Kubeflow features within a single KFP pipeline, including Dask for parallel batch preprocessing, Katib for hyperparameter tuning, PyTorch Operator for multi-node/multi-GPU model training, and KServe for deployment. Gain practical insights into applying these powerful tools in a technically demanding environment, showcasing the combined effectiveness of Kubeflow's collection of ML software development and deployment tools. Discover how to leverage Kubeflow's capabilities for real-world scenarios, enhancing your understanding of cloud native computing and machine learning workflows.

Efficient Integration of Kubeflow Tools: An ISS Data Case Study on Anomaly Detection