Azure Synapse Analytics End to End Machine learning — Model Development

Azure Synapse Analytics End to End Machine learning — Model Development

Load the data from the data source in this case the sample dataset Data Processing (ETL) using Pyspark.ETL work done in conjunction with pyspark and Spark SQL dataframe

Use Case

  • Load data from data source in this case sample dataset
  • Process data (ETL) using Pyspark
  • ETL work is done in combination with pyspark dataframe and Spark SQL
  • Save processed data into Synapse dedicated SQLPools
  • Resume and Pause dedicated SQL pools as we run ETL
  • Save a copy in default storage for serverless activities
  • Build and Train Machine learning model
  • We are using same notebook as pyspark but building with scala code
  • Build different Pipeline for Resuming and Pausing dedicated SQL Pools

data-science azure-synapse-analytics

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