Exploring Data in Azure Machine Learning
Exploring Data in Azure Machine Learning looks at using Jupyter Notebooks to interactively explore and manipulate data prior to model training. In this lesson, we learn how to get a basic statistical summary of data and then how to resolve missing data values. The lesson’s demonstrations cover two scenarios: data sourced from a storage account and data from an attached Spark pool.
Learning Objectives
- Learn how to use the AzCopy utility to copy files to blob storage
- Learn how to use the Python SDK within a notebook to query and manipulate the data
Intended Audience
- Those interested in learning how to set up Azure Machine Learning Studio for interactive data wrangling
Prerequisites
- General understanding of the data store and data asset topics covered in the Accessing Data in Azure Machine Learning Lesson
Hallam is a software architect with over 20 years experience across a wide range of industries. He began his software career as a Delphi/Interbase disciple but changed his allegiance to Microsoft with its deep and broad ecosystem. While Hallam has designed and crafted custom software utilizing web, mobile and desktop technologies, good quality reliable data is the key to a successful solution. The challenge of quickly turning data into useful information for digestion by humans and machines has led Hallam to specialize in database design and process automation. Showing customers how leverage new technology to change and improve their business processes is one of the key drivers keeping Hallam coming back to the keyboard.