Understanding the big picture of NAS

Before we dive into the details of the big picture of NAS methods, it’s important to note that although NAS minimizes the manual effort necessary for shaping the final architecture, it doesn’t completely negate the need for expertise in the field. As we discussed earlier, foundational knowledge in deep learning (DL) is crucial for selecting appropriate search spaces and interpreting the results of NAS accurately. Search spaces are the set of possible options or configurations that can be explored during a search. Furthermore, the performance of NAS heavily relies on the quality of the training data and the relevance of the search space to the task at hand. Therefore, domain expertise is still necessary to ensure that the final architecture is not only efficient but also accurate and relevant to the problem being solved. By the end of this section, you will have a better understanding of how to leverage your domain expertise to optimize...