What’s new for machine learning in Microsoft R Server

-
Microsoft R Server 9.1.0, Microsoft's R distribution with added big-data, in-database, and integration capabilities, is released in April 2017 and is available for download. The release has several exciting features, including new machine-learning capabilities to support text and image processing and improved operationalization. The update includes new functionality to MicrosoftML. This package provides state-of-the-art, fast and scalable machine learning algorithms for common data science tasks including featurization, classification and regression. Some of the new functions include:

Added support for most MRS platforms including Spark,
, and Linux
Out of the box image featurization with several deep neural pre-trained models
Easy to use sentiment analysis functionality
Support for Ensembling and parallel learning
Improved operationalization on web and SQL

Comments

Post a Comment

Popular posts from this blog

new machine learning package for Microsoft R Server

-
Image
MicrosoftML (MML) is a new machine learning package for Microsoft R Server. Microsoft R Server brings you the ability to do parallel and chunked data processing that addresses the restrictions of in-memory open source R. MML adds Microsoft's battle-tested algorithms and data transforms that are used by product teams across Microsoft. This brings new machine learning functionality with increased speed, performance and scale, especially for handling a large corpus of text data and high-dimensional categorical data. MML includes the ability to: Create text classification models for problems such as sentiment analysis and support ticket classification. Train deep neural nets in order to solve complex problems such as retail image classification and handwriting analysis. Work with high-dimensional data for scenarios like online advertising click-through prediction. Solve many other common machine learning tasks such as churn prediction, loan risk analysis, and demand forecasting ...
Read more

Machine Learning Services (R, Python) in SQL Server 2017

-
                Machine Learning Service (R,Python )in SQL Server 2017   SQL Server 2017 Machine Learning Services is an add-on to a database engine instance, used for executing R and Python code on SQL Server. The feature includes microsoft R python packages  for high-performance predictive analytics and machine learning. Code runs in an extensibility framework, isolated from core engine processes, but fully available to relational data as stored procedures, as T-SQL script containing R or Python statements, or as R or Python code containing T-SQL. If you previously used , Machine Learning SQL server 2016 R service  in SQL Server 2017 is the next generation of R support, with updated versions of base R, RevoScaleR, MicrosoftML, and other libraries introduced in 2016. In Azure SQL Database machine learning service with R is currently in public preview.  Bring  compute power to the data The key value proposi...
Read more

Optimizations in Syntax Highlighting

-
Image
Optimizations in Syntax Highlighting Visual Studio Code version 1.9 includes a cool performance improvement that we've been working on and I wanted to tell its story. TL;DR  TextMate themes will look more like their authors intended in VS Code 1.9, while being rendered faster and with less memory consumption. Syntax Highlighting Syntax Highlighting usually consists of two phases. Tokens are assigned to source code, and then they are targeted by a theme, assigned colors, and voilà, your source code is rendered with colors. It is the one feature that turns a text editor into a code editor. Tokenization in VS Code (and in the  Monaco Editor ) runs line-by-line, from top to bottom, in a single pass. A tokenizer can store some state at the end of a tokenized line, which will be passed back when tokenizing the next line. This is a technique used by many tokenization engines, including TextMate grammars, that allows an editor to retokenize only a small subset of the line...
Read more