Google AutoML is a suite of machine learning tools designed to simplify the process of training high-performance deep networks. It leverages advanced techniques such as Neural Architecture Search (NAS) to automatically find the most suitable neural network architecture for a given dataset and task. This means that users do not need extensive knowledge of deep learning; they only need to provide labeled data to get started ¹.

However, there are some considerations to keep in mind. Using Google AutoML can be costly, with charges of around USD $20 per hour for computer vision tasks. Additionally, there is no guarantee that the performance will surpass that of a hand-designed network, which may lead to uncertainty regarding the investment ¹.

While Google AutoML offers a powerful solution, it may not be the best fit for everyone, especially smaller companies or startups that may lack the necessary computing resources ⁴.

If you’re interested in exploring AutoML further, you might want to consider alternatives like open-source options, such as AutoKeras, which can provide similar functionalities without the associated costs ¹.