AutoML comes into play when pretrained models are not fit for purpose. As an example, the Vision API can recognize a table, but what if we want to recognize a particular table that our company produces? The Vision API cannot do that for us.
In such a case, we need to use AutoML or train our own model. As you have probably already guessed, the former is a much easier method. What AutoML does is it takes datasets from you, trains and deploys the model, and then serves it through the REST API. This sounds a little bit like magic, right? Take a look at the following diagram:
Note that there are five services available that allow you to train your custom model:
- AutoML Vision: This classifies your images according to your own defined labels.
- AutoML Translation: This performs translation queries, returning results specific to your domain.
- AutoML Natural Language: This classifies...
