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Google Cloud Certified Professional Machine Learning Engineer · Google Cloud
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Transfer Learning (The AutoML Secret): Google has already trained a "base" model on a massive amount of data (like all of Wikipedia and Google News). This model already understands what words mean and how sentences are structured. AutoML only needs your data to learn the "final layer." It just needs to see a few examples of your custom categories to figure out how they differ from each other.
AutoML frequently uses transfer learning, especially for deep learning tasks like image recognition. It is one of the core techniques that enables AutoML to train high-quality models quickly and with smaller datasets. Instead of building a deep learning model from scratch, AutoML starts with a pre-trained model that has already learned to recognize features from a massive dataset, like ImageNet for images.
You do not have enough data to train a model from scratch. AutoML needs training data.