Mounting the dataset in ML Workspace

V JEEVA 46 Reputation points
2022-08-25T06:25:27.513+00:00

How to mount the dataset in ML Studio using python sdk ?
What are the different ways and which is the right one ?

Can we create dataset pointing to two different stores ?

Also where can I learn more about azure machine learning ?

Azure Machine Learning
Azure Machine Learning
An Azure machine learning service for building and deploying models.
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  1. YutongTie-MSFT 46,091 Reputation points
    2022-08-25T23:18:32.52+00:00

    Hello @V JEEVA

    Thanks for using Microsoft Q&A platform. Let me answer your questions one by one.

    where can I learn more about azure machine learning
    The best way to learn Azure Machine Learning is the documentation, please refer to - https://azure.microsoft.com/en-us/services/machine-learning/#documentation

    How to mount the dataset in ML Studio using python sdk ?
    Generally there are two ways to work with data in Azure Machine Learning -
    Use datastores - https://learn.microsoft.com/en-us/azure/machine-learning/how-to-datastore?tabs=cli-identity-based-access%2Ccli-adls-identity-based-access%2Ccli-azfiles-account-key%2Ccli-adlsgen1-identity-based-access
    Use data assets - https://learn.microsoft.com/en-us/azure/machine-learning/how-to-datastore?tabs=cli-identity-based-access%2Ccli-adls-identity-based-access%2Ccli-azfiles-account-key%2Ccli-adlsgen1-identity-based-access

    What are the different ways and which is the right one ?
    It depends on your need. Compared to data assets and datastore, the benefits of creating data assets are:
    You can share and reuse data with other members of the team such that they do not need to remember file locations.
    You can seamlessly access data during model training (on any supported compute type) without worrying about connection strings or data paths.
    You can version the data.

    Can we create dataset pointing to two different stores ?
    If you need to assembly data, you may want to consider data assets. By creating a data asset, you create a reference to the data source location, along with a copy of its metadata. Because the data remains in its existing location, you incur no extra storage cost, and don't risk the integrity of your data sources. You can create Data from datastores, Azure Storage, public URLs, and local files.

    I hope this helps!

    Regards,
    Yutong

    -Please kindly accept the answer if you feel helpful to support the community, thanks a lot.

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