microsoftml (Python package in SQL Server Machine Learning Services)

Applies to: SQL Server 2017 (14.x) and later

microsoftml is a Python package from Microsoft that provides high-performance machine learning algorithms. It includes functions for training and transformations, scoring, text and image analysis, and feature extraction for deriving values from existing data. The package is included in SQL Server Machine Learning Services and supports high performance on big data, using multicore processing, and fast data streaming.

Package details Information
Current version: 9.4
Built on: Anaconda 4.2 distribution of Python 3.7.1
Package distribution: SQL Server Machine Learning Services version 2017 or 2019.

How to use microsoftml

The microsoftml module is installed as part of SQL Server Machine Learning Services when you add Python to your installation. You get the full collection of proprietary packages plus a Python distribution with its modules and interpreters. You can use any Python IDE to write Python script calling functions in microsoftml, but the script must run on a computer having SQL Server Machine Learning Services with Python.

Microsoftml and revoscalepy are tightly coupled; data sources used in microsoftml are defined as revoscalepy objects. Compute context limitations in revoscalepy transfer to microsoftml. Namely, all functionality is available for local operations, but switching to a remote compute context requires RxSpark or RxInSQLServer.

Versions and platforms

The microsoftml module is available only when you install one of the following Microsoft products or downloads:


Full product release versions are Windows-only in SQL Server 2017. Both Windows and Linux are supported for microsoftml in SQL Server 2019.

Package dependencies

Algorithms in microsoftml depend on revoscalepy for:

  • Data source objects - Data consumed by microsoftml functions are created using revoscalepy functions.
  • Remote computing (shifting function execution to a remote SQL Server instance) - The revoscalepy package provides functions for creating and activating a remote compute context for SQL Server.

In most cases, you will load the packages together whenever you are using microsoftml.

Functions by category

This section lists the functions by category to give you an idea of how each one is used. You can also use the table of contents to find functions in alphabetical order.

1-Training functions

Function Description
microsoftml.rx_ensemble Train an ensemble of models.
microsoftml.rx_fast_forest Random Forest.
microsoftml.rx_fast_linear Linear Model. with Stochastic Dual Coordinate Ascent.
microsoftml.rx_fast_trees Boosted Trees.
microsoftml.rx_logistic_regression Logistic Regression.
microsoftml.rx_neural_network Neural Network.
microsoftml.rx_oneclass_svm Anomaly Detection.

2-Transform functions

Categorical variable handling

Function Description
microsoftml.categorical Converts a text column into categories.
microsoftml.categorical_hash Hashes and converts a text column into categories.

Schema manipulation

Function Description
microsoftml.concat Concatenates multiple columns into a single vector.
microsoftml.drop_columns Drops columns from a dataset.
microsoftml.select_columns Retains columns of a dataset.

Variable selection

Function Description
microsoftml.count_select Feature selection based on counts.
microsoftml.mutualinformation_select Feature selection based on mutual information.

Text analytics

Function Description
microsoftml.featurize_text Converts text columns into numerical features.
microsoftml.get_sentiment Sentiment analysis.

Image analytics

Function Description
microsoftml.load_image Loads an image.
microsoftml.resize_image Resizes an Image.
microsoftml.extract_pixels Extracts pixels from an image.
microsoftml.featurize_image Converts an image into features.

Featurization functions

Function Description
microsoftml.rx_featurize Data transformation for data sources

Scoring functions

Function Description
microsoftml.rx_predict Scores using a Microsoft machine learning model

How to call microsoftml

Functions in microsoftml are callable in Python code encapsulated in stored procedures. Most developers build microsoftml solutions locally, and then migrate finished Python code to stored procedures as a deployment exercise.

The microsoftml package for Python is installed by default, but unlike revoscalepy, it is not loaded by default when you start a Python session using the Python executables installed with SQL Server.

As a first step, import the microsoftml package, and import revoscalepy if you need to use remote compute contexts or related connectivity or data source objects. Then, reference the individual functions you need.

from microsoftml.modules.logistic_regression.rx_logistic_regression import rx_logistic_regression
from revoscalepy.functions.RxSummary import rx_summary
from revoscalepy.etl.RxImport import rx_import_datasource

See also