You are developing a model to identify traffic signs in images extracted from videos taken from the dashboard
of a vehicle. You have a dataset of 100 000 images that were cropped to show one out of ten different traffic
signs. The images have been labeled accordingly for model training and are stored in a Cloud Storage bucket
You need to be able to tune the model during each training run. How should you train the model?
You work for a retail company. You have a managed tabular dataset in Vertex Al that contains sales data from
three different stores. The dataset includes several features such as store name and sale timestamp. You want
to use the data to train a model that makes sales predictions for a new store that will open soon You need to
split the data between the training, validation, and test sets What approach should you use to split the data?
You are collaborating on a model prototype with your team. You need to create a Vertex Al Workbench
environment for the members of your team and also limit access to other employees in your project. What
should you do?
You are developing ML models with Al Platform for image segmentation on CT scans. You frequently update
your model architectures based on the newest available research papers, and have to rerun training on the same
dataset to benchmark their performance. You want to minimize computation costs and manual intervention
while having version control for your code. What should you do?
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