Hi,
Thanks for reaching out. With the new Azure ML (Preview), you can you can register
your data or use the import data module to import data from online data sources.
Datastore represents a storage abstraction over an Azure Machine Learning storage account. They are used to store
connection information to Azure storage services so you can refer to them by name and don't need to remember the connection information and secret used to connect to the storage services.
Dataset is a reference to data in a Datastore or behind public web urls. They are supported in two formats (Tabular
and File).
After
creating your datastore, you then
create/register your dataset (accessible both locally and remotely on compute clusters like the Azure Machine Learning compute. Note: you can also create an unregistered dataset and use as direct input in experiments. However, if you want to reuse the dataset
in other experiments, you need to register the dataset. Please check out
Use datasets directly in training scripts and
Mount files to remote compute targets for more details. The following
Notebook Examples demonstrate and expand further on these concepts. Hope these resources are helpful to you. Thanks.
Regards,
GiftA-MSFT.
If a post helps to resolve your issue, please click “Mark
as Answer” and/or “Vote as helpful”.
By marking a post as Answered and/or Helpful, you help others find the answer faster. Thanks.
