EndtoEndDSLab

End-to-End Azure Data & Analytics Offering

It helped to demonstrate:

1. End-to-End Azure Data & Analytics Offering
2. Ease of Implementation and Integration based on a real world use case relevance – Deploying a Binary Classification Model
3. In-line with the End-to-End Data Science Process i.e. Data Ingestion, Exploration, Sampling, Feature Engineering, Modelling and Operationalising the Model i.e. through Web Services https://azure.microsoft.com/en-us/documentation/learning-paths/data-science-process/

Azure Tools / Technologies Used

Azure Data Lake Store / Analytics, U-SQL, Data Science VM, ADF, AML, Jupyter Notebooks, Python)