Running summarizing tools on a new article

Abstract: This chapter describes the process of building and deploying some of the time series forecasting solutions by employing some of the use cases and data sets. It uses Azure Machine Learning SDK for Python to build and run machine learning workflows. The chapter provides a summary of some of the most important classes in the SDK that readers can use to build their time series forecasting solution: readers can find all information about the classes below on the official website of Azure Machine Learning SDK for Python. It aims to build, train, and deploy an energy demand forecasting solution on Azure. The chapter talks more about machine learning model deployment, that is, the method of integrating a machine learning model into an existing production environment in order to begin developing practical business decisions based on data.