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Answer: Train your model with DLVM images on Vertex AI, and ensure that your code utilizes NumPy and SciPy internal methods whenever possible.
The best initial approach for improving the training time of a scikit-learn model when migrating to Google Cloud Vertex AI is to train the model with DLVM images on Vertex AI and ensure that your code utilizes NumPy and SciPy internal methods whenever possible. Scikit-learn does not support GPU training natively, making Option D less effective. Optimizing code with DLVM images is more appropriate and can yield improvements without requiring a complete migration to TensorFlow or setting up distributed computing environments.
Author: LeetQuiz Editorial Team
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You have developed a machine learning model using scikit-learn, but you are experiencing longer than expected training times. To address this issue, you decide to migrate your model to Vertex AI Training offered by Google Cloud. Your goal is to improve the training time of the model. Based on this scenario, what should you try first to achieve your goal?
A
Migrate your model to TensorFlow, and train it using Vertex AI Training.
B
Train your model in a distributed mode using multiple Compute Engine VMs.
C
Train your model with DLVM images on Vertex AI, and ensure that your code utilizes NumPy and SciPy internal methods whenever possible.
D
Train your model using Vertex AI Training with GPUs.
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