G2

Subhashree S.

Developer

Computer Software

Enterprise (> 1000 emp.)

8/10/2026

"Google Cloud AutoML Makes Building and Deploying ML Models Easy"

4.5/5

What do you like best about Google Cloud AutoML?

What I like best about Google Cloud AutoML is that it makes it much easier to build and deploy machine learning models without having to handle every part of the ML pipeline manually. The interface is fairly straightforward, and it’s useful for quickly testing models and getting a baseline without needing to be an expert in model development. It also fits well with other Google Cloud services, which makes it easier to use in existing cloud workflows. Review collected by and hosted on G2.com.

What do you dislike about Google Cloud AutoML?

The main thing I dislike is that AutoML can feel a bit limiting when you need more control over the model or want to customize the training process. Some of the advanced options are not as flexible as building and training a model yourself. It can also become relatively expensive when running larger datasets or multiple training experiments. Review collected by and hosted on G2.com.

What problems is Google Cloud AutoML solving and how is that benefiting you?

Google Cloud AutoML helps us reduce the amount of time and effort needed to build and test machine learning models. We can get models trained and evaluated without having to manage the entire ML pipeline from scratch, which is especially useful for quick prototypes and smaller ML use cases. It helps us get experiments into a usable state faster and lets the team focus more on the actual business problem rather than infrastructure and model setup. Review collected by and hosted on G2.com.