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Google Cloud Certified Professional Machine Learning Engineer · Google Cloud
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Choose a GPU type: Start with NVIDIA T4 for cost-efficiency or A100 for high performance. Spin up a Deep Learning VM: Use the Google Cloud Console or gcloud CLI. Upload your code and data: You can use Cloud Storage buckets or SCP. Train and monitor: Use TensorBoard or logging to monitor convergence.
Not A: the model may not be compatible with TPU -- there are specific requirements for this. Not B: 8 GPUs seems overkill as next step. Not D: GPU will very likely perform better than CPU C: Good idea to try some GPU and observe the speedup. Try first with pre-installed libraries for easier experimentation -- trim down or specialize later if needed.
C is wrong because n1‐standard‐2 is too small for GPUs.