revoscalepy is a

machine learning Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine ...

package in Python created by

Microsoft Microsoft Corporation is an American multinational corporation, multinational technology company, technology corporation producing Software, computer software, consumer electronics, personal computers, and related services headquartered at th ...

. It is available as part of Machine Learning Services in

Microsoft SQL Server Microsoft SQL Server is a relational database management system developed by Microsoft. As a database server, it is a software product with the primary function of storing and retrieving data as requested by other software applications—which ...

2017 and Machine Learning Server 9.2.0 and later. The package contains functions for creating

linear model In statistics, the term linear model is used in different ways according to the context. The most common occurrence is in connection with regression models and the term is often taken as synonymous with linear regression model. However, the term ...

logistic regression In statistics, the logistic model (or logit model) is a statistical model that models the probability of an event taking place by having the log-odds for the event be a linear function (calculus), linear combination of one or more independent var ...

random forest Random forests or random decision forests is an ensemble learning method for classification, regression and other tasks that operates by constructing a multitude of decision trees at training time. For classification tasks, the output of th ...

decision tree A decision tree is a decision support tool that uses a tree-like model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one way to display an algorithm that only contains co ...

and boosted decision tree, in addition to some summary functions for inspecting data. Other machine learning algorithms such as neural network are provided in microsoftml, a separate package that is the Python version of MicrosoftML. revoscalepy also contains functions designed to run machine learning

algorithm In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing ...

s in different compute contexts, including SQL Server,

Apache Spark Apache Spark is an open-source unified analytics engine for large-scale data processing. Spark provides an interface for programming clusters with implicit data parallelism and fault tolerance. Originally developed at the University of Califor ...

, and

Hadoop Apache Hadoop () is a collection of open-source software utilities that facilitates using a network of many computers to solve problems involving massive amounts of data and computation. It provides a software framework for distributed storage ...

. In June 2021, Microsoft announced to open source the revoscalepy and

RevoScaleR RevoScaleR is a machine learning package in R created by Microsoft. It is available as part of Machine Learning Server, Microsoft R Client, and Machine Learning Services in Microsoft SQL Server 2016. The package contains functions for creating l ...

packages, making them freely available under the

MIT License The MIT License is a permissive free software license originating at the Massachusetts Institute of Technology (MIT) in the late 1980s. As a permissive license, it puts only very limited restriction on reuse and has, therefore, high license co ...

.Looking to the future for R in Azure SQL and SQL Server - Microsoft SQL Server Blog
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References

External links

Samples for using revoscalepy and microsoftml
{{Microsoft FOSS Applied machine learning Python (programming language) software Microsoft software

See also

References

External links