Datasets include public-domain data for weather, census, holidays, public safety, and location that help you train machine learning models and enrich predictive solutions. You can also share your public datasets on Azure Open Datasets.
Curated open public datasets in Azure Open Datasets are optimized for consumption in machine learning workflows.
Data scientists often spend the majority of their time cleaning and preparing data for advanced analytics. Open Datasets are copied to the Azure cloud and preprocessed to save you time. At regular intervals data is pulled from the sources, such as by an FTP connection to the National Oceanic and Atmospheric Administration (NOAA), parsed into a structured format, and then enriched as appropriate with features such as ZIP Code or location of the nearest weather station.
Datasets are cohosted with cloud compute in Azure making access and manipulation easier.
Following are examples of datasets available.
|NOAA Integrated Surface Data (ISD)||Azure Notebooks
|Worldwide hourly weather data from NOAA with the best spatial coverage in North America, Europe, Australia, and parts of Asia. Updated daily.|
|NOAA Global Forecast System (GFS)||Azure Notebooks
|15-day U.S. hourly weather forecast data from NOAA. Updated daily.|
|Public Holidays||Azure Notebooks
|Worldwide public holiday data, covering 41 countries or regions from 1970 to 2099. Includes country and whether most people have paid time off.|
With an Azure account, you can access open datasets using code or through the Azure service interface. The data is colocated with Azure cloud compute resources for use in your machine learning solution.
Open Datasets provides Azure Notebooks and Azure Databricks notebooks you can use to connect data to Azure Machine Learning service and Azure Databricks. Datasets can also be accessed through a Python SDK.
However, you don't need an Azure account to access Open Datasets; you can access them from any Python environment without or without Spark.
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