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SwatiGharse
Microsoft
MicrosoftAutomated ML models for computer vision tasks require GPU SKUs and support NC and ND families. We recommend the NCsv3-series (with v100 GPUs) for faster training. A compute target with a multi-GPU VM SKU leverages multiple GPUs to also speed up training. Additionally, when you set up a compute target with multiple nodes you can conduct faster model training through parallelism when tuning hyperparameters for your model.
Thanks Swati,
I work for a startup. We do not need the fastest training. We are willing to wait. What we need is the most cost efficient SKU.
Do you have a recommendation for most cost efficient sku for Assisted Labeling and Object Detection Model training?
- cesardlHere you have a couple of links explaining compute in Azure ML: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-create-attach-compute-cluster?tabs=python https://docs.microsoft.com/en-us/azure/machine-learning/how-to-create-manage-compute-instance?tabs=python
- Can you point me to something in these docs that tells me which of the vms listed in the add quota list will be the most cost efficient? Thanks.
