Attendees
| Sl. No. | Topic | Presenter | Notes |
|---|---|---|---|
| 1 | Data Generation | Failure and Anomaly Data Generation The Data can also be used for ITU challenge. Please share your inputs in the above link - Its an experiment! | |
| 2 | Log-Analysis - Status Update | Moved to next week. | |
| 3 | Update on KubeFlow and GANs | Trying: Acumos and Kubeflow. Kubeflow: Ease to use. Support multiple cloud (AWS, GCP). First the K8S cluster is deployed, and on that Kubeflow Pods are deployed. arrikto - Knowledge sharing on Kubeflow. By default, simple models (linear regression, SVMs, etc) are available. Library support: TF and PyTorch. Data-Pipeline Integration Support: Prometheus. Elasticsearch. ToDo: Migrate the FP model to KubeFlow. Next Week: How to Add new Model to Kubeflow.? GANs: Slight improvement with Cycle-GANs, work is ongoing. | |
| 4 | ITU Challenge Update | Document to submit ready. We will ready with the data by March. | |
| 5 |