Category: .NET/Visual Studio

Microsoft recently released a preview of a machine learning framework for .NET developers—ML.NET. I needed to perform a clustering analysis from existing data in one of my applications. This is a pretty common machine learning task, so I decided to document the basic approach in this article. We’ll use the well-worn iris data set from […]

One of the products Microsoft introduced at their 2018 Build conference was an open source, cross-platform machine learning framework for .NET developers. ML.NET will …allow .NET developers to develop their own models and infuse custom ML into their applications without prior expertise in developing or tuning machine learning models. Democratisation of machine learning—-i.e. enabling people […]

Part 2: Controlling Parameter Optimization with Plan Guides For Part 1 of this series, see LINQ: The Good, The Bad, and The Poorly Optimized. T-SQL supports a variety of “hints”. They are hints in the same sense that your mother used to hint that it’s time to wash up and come to dinner. In other […]

Part I: LINQ and sp_executesql Numerous questions raised in numerous forums mention that LINQ to SQL wraps queries in a call to the stored procedure sp_executesql. There seems to be agreement that this is done to ensure the caching of the query and query parameterization (if, indeed, parameters are supplied). Some advantages to sp_executesql, like […]

Down the Rabbit Hole with RODBC The most direct method for reading SQL Server data into the statistical program R is with ODBC. If R is running on a Windows system, this is straightforward using the R package RODBC. On a Linux system, the installation of RODBC is more challenging. Of course, RODBC requires a […]