SQL Server 2017 Machine Learning Services with R: Data exploration, model – GOOD

SQL Server 2017 Machine Learning Services with R: Data exploration, model – GOOD

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In this post, we will be discussing the SQL Server 2017 Machine Learning Services with R, focusing on data exploration and model building.

SQL Server 2017 introduces the ability to run R scripts directly within the database engine, allowing for seamless integration of machine learning capabilities with your existing SQL Server infrastructure.

Data exploration is a crucial step in any machine learning project, as it allows us to better understand the patterns and relationships within our data. With SQL Server 2017 Machine Learning Services, we can easily explore our data using R scripts, visualizations, and statistical functions directly within the database. This simplifies the process of data exploration and helps us uncover valuable insights that can inform our model building process.

When it comes to building machine learning models, SQL Server 2017 Machine Learning Services with R offers a comprehensive set of tools and functions to help us create, train, and evaluate our models. From regression and classification to clustering and time series forecasting, we can leverage the power of R to build sophisticated models that can make accurate predictions and drive business decisions.

Overall, SQL Server 2017 Machine Learning Services with R provides a powerful and efficient platform for data exploration and model building, offering a seamless integration of R capabilities within the SQL Server environment. Whether you are a data scientist, developer, or business analyst, this feature can help you unlock the full potential of your data and drive innovation within your organization.
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