You built a custom ML model using scikit-learn. Training time is taking longer than expected. You decide to migrate your model to Vertex AI Training, and you want to improve the model’s training time. What should you try out first?
You built a custom ML model using scikit-learn. Training time is taking longer than expected. You decide to migrate your model to Vertex AI Training, and you want to improve the model’s training time. What should you try out first?
Scikit-learn, the library in question, does not natively support GPU training. It is specifically designed to run on CPUs. While distributed computing can speed up training time for large datasets, the first step should be training your model using Vertex AI Training with CPUs to leverage any optimizations and scalability offered by Vertex AI specifically for CPU-based training.
SK-Learn offers no GPU support. Answer is B!
B is correct, because scikit only has CPU support for the following services: - prebuilt containers for custom training (this is the case here) - prebuilt containers for predictions and explanations - Vertex AI Pipelines - Vertex AI Workbench user-managed notebooks https://cloud.google.com/vertex-ai/docs/supported-frameworks-list#scikit-learn_2
B. Train your model using Vertex AI Training with CPUs. No GPUs for ScikitLearn, but parrallelize/distribute training is a good way to increase model building
Why no A?
GPU helps speeding up training process
Scikit-learn doesn't natively support GPUs for training. However, many scikit-learn algorithms rely on libraries like NumPy and SciPy. These libraries can leverage GPUs if they're available on the system, potentially benefiting scikit-learn models indirectly.
scikit-learn no GPU support.
You decided to migrate to Vertex AI, If you have a model that requires significant computational resources and doesn't rely heavily on specialized GPU operations (like those in option D), then option B might still be a good choice. However, if your model is computationally intensive or involves complex neural network architectures I would go with D instead of B.
Scikit-learn is not intended to be used as a deep-learning framework and it does not provide any GPU support. (Ref: https://stackoverflow.com/questions/41567895/will-scikit-learn-utilize-gpu). So I go with B