I have a somewhat off-topic question as a complete TensorFlow beginner and it seems like you'd be in the know:
If I want to train a TF model distributed over many machines in GCP, it seems like I could use Cloud ML Engine or deploy Kubeflow to a K8s cluster running in GKE and train it there.
What should I consider when choosing between these two options? Is there another option I should consider?
If I want to train a TF model distributed over many machines in GCP, it seems like I could use Cloud ML Engine or deploy Kubeflow to a K8s cluster running in GKE and train it there.
What should I consider when choosing between these two options? Is there another option I should consider?