Google open-sourced its AutoML framework for model architecture search at scale.
It helps to find the right model architecture for any classification problems (i.e., CNN with different types of layers).
Now you can write fit(); predict() and call it a day! Of course, in case you have enough GPUs 🙊😅

You can define your own model building blocks to use for search as well.
The framework uses Bayesian optimization to find proper hyperparameters and can build an ensemble of the models.
Works both for table and image data.

https://github.com/google/model_search