Automated machine learning (AutoML) refers to those applications that are able to automate the end-to-end process of applying machine learning to real-world problems. Generally, scientific analysts must process data through a series of preliminary procedures before submitting it to machine learning algorithms. In the previous chapters, you saw the necessary steps for performing a proper analysis of data through these algorithms. You saw how simple it is to build a model based on deep neural networks by using several libraries. In some cases, these skills are beyond those possessed by analysts, who must seek support from industry experts to solve the problem.
AutoML was born from a need to create an application that automated the whole machine learning process so that the user could take advantage of these services. Generally, machine learning experts must perform...
