In a previous article I discussed the various methods available in SQL Server 2016 & 2017 to perform in-database analytics. In the article I used a model that was stored directly inside SQL Server to perform predictions. But what if your models are not stored inside SQL Server but are build inside Azure Machine Learning? […]

When you are working with Machine Learning there are many things you need to keep an eye on. You need to prepare the data, deal with any missing values and you need to select an algorithm you will be using for you model. Choosing an algorithm can be a difficult one though. Azure Machine Learning […]

With Azure Machine Learning (AzureML) you have access to a cloud based, flexible and friendly method to perform machine learning tasks on your data. One disadvantage I frequently run into is that cloud based approach of AzureML since the data you are building your machine learning models on has to be in the cloud as […]