Data can be imported into ML Studio through
Answers
Here are some of the sources you can use to import and export data and models in Machine Learning Studio:
Get data from sources in the cloud, such as Azure SQL Database, Azure SQL Data Warehouse, Azure Storage, and Azure Cosmos DB. You can also import data that's provided as a public web URL, get data from Hadoop by using a Hive query, or query an on-premises SQL server.
Load a collection of images from Azure Blob storage to use in image classification tasks.
Extract the data from zipped files that you uploaded to Machine Learning. You can use the datasets in experiments.
Create small datasets by typing in the Machine Learning Studio UI. This can be handy for creating small test datasets.
Save your results or intermediate data to Azure Table storage, Blob storage, a SQL database, or a Hive query.
Get a trained model from a URL or Blob storage, and then use it in an experiment.
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To use your own data in Machine Learning Studio to develop and train a predictive analytics solution, you can use data from:
Local file - Load local data ahead of time from your hard drive to create a dataset module in your workspace
Online data sources - Use the Import Data module to access data from one of several online sources while your experiment is running
Machine Learning Studio experiment - Use data that was saved as a dataset in Machine Learning Studio