The increasing diversification of the type and volume of data, the lowering of computational processing costs and storage costs have opened a window of opportunity for the resurgence of a discipline that already existed on paper and among equations: Machine Learning.
Most of the content of this post is platform-agnostic. Since in these days I’m using Azure Machine Learning, I take it as a starting point of my studies.
It’s quite simple for an Azure Machine Learning average user to create a regression experiment, make the data flow in it and get the predicted values. It’s also easy to have some metrics to evaluate the implemented model. Once you get them, the following questions arise: (more…)