SQL Server Machine Learning Services: Python
Offered By: LinkedIn Learning
Course Description
Overview
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
- 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
- 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
- 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
- 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
- Create a Python stored procedure
- Parameterize the procedure
- Challenge: Write a stored procedure
- Solution: Write a stored procedure
- Install MLS on a standalone server
- Add development tools to the client
- Work with Jupyter Notebooks
- Next steps
Taught by
Adam Wilbert
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