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 them to machine learning algorithms. In previous chapters, we have seen the necessary steps for performing proper analysis of data through these algorithms. We have seen how simple it is to build a model based on deep neural networks using Keras. In some cases, these skills are outside those possessed by analysts, who must seek support from industry experts to solve the problem. AutoML was born from the need to create an application that automates the whole machine learning process, so that the user can take advantage of these services.
Generally, machine learning experts must perform...
