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LinkedIn Learning

SQL Server Machine Learning Services: Python

via LinkedIn Learning

Overview

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Learn how to analyze SQL Server data with Python. Discover how to perform statistical analyses, generate graphics, and process tabular data—directly in SQL Server.

Syllabus

Introduction
  • Analyze SQL Server data with Python
  • What you should know
  • Using the exercise files
1. Get Started with MLS
  • What is machine learning services?
  • Install ML services for Python
  • Enable script execution in SQL Server
  • Use variables in Python
  • Create a Python while loop
2. Write Python Scripts for SQL Server
  • Import a dataset from SQL Server
  • Manipulate a data frame
  • Output a result set to SQL Server
  • Python syntax pitfalls
  • Challenge: Import a data frame
  • Solution: Import a data frame
3. Python Package Modules and Libraries
  • The Anaconda open-source packages
  • Functions in the revoscalepy package
  • Model, train, and score with microsoftml
  • Produce graphics with MatPlotLib
  • Get descriptive statistics with pandas
  • Challenge: Sample a data frame
  • Solution: Sample a data frame
4. Processing Tabular Data
  • Return values with indexes and series
  • Convert a series to a data frame
  • Add multiple series to a data frame
  • Include the index in a data frame
  • Slice a data frame to series
  • Challenge: Import and process data
  • Solution: Import and process data
5. Create a SQL Stored Procedure
  • Create a Python stored procedure
  • Parameterize the procedure
  • Challenge: Write a stored procedure
  • Solution: Write a stored procedure
6. Create an External Data Science Client
  • Install MLS on a standalone server
  • Add development tools to the client
  • Work with Jupyter Notebooks
Conclusion
  • Next steps

Taught by

Adam Wilbert

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