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Answer: Use Vertex AI Pipelines with TensorFlow Extended (TFX) to create a pipeline that reads the images from Cloud Storage and trains the model.
The correct answer is B. Using Vertex AI Pipelines with TensorFlow Extended (TFX) to create a pipeline that reads the images from Cloud Storage and trains the model is the most appropriate approach. TFX is tightly integrated with TensorFlow, provides convenient APIs for reading data directly from GCS buckets, and offers higher-level abstractions and components designed for common machine learning tasks. This makes it a more suitable option compared to other choices that either involve more complex or less streamlined processes.
Author: LeetQuiz Editorial Team
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You are tasked with developing an image classification model using a large dataset of labeled images stored in a Cloud Storage bucket. This process involves reading the images, training the model, and possibly utilizing managed datasets or pipelines to streamline the workflow. Given these requirements, what should you do?
A
Use Vertex AI Pipelines with the Kubeflow Pipelines SDK to create a pipeline that reads the images from Cloud Storage and trains the model.
B
Use Vertex AI Pipelines with TensorFlow Extended (TFX) to create a pipeline that reads the images from Cloud Storage and trains the model.
C
Import the labeled images as a managed dataset in Vertex AI and use AutoML to train the model.
D
Convert the image dataset to a tabular format using Dataflow, load the data into BigQuery, and use BigQuery ML to train the model.
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