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2. Structured data classification with a Wide & Deep model, with distributed hyperparameter tuning:https://www.kaggle.com/nitric/hp-tuning-wide-and-deep-model-using-google-cloud …
To get started with TensorFlow Cloud, first you'll need to configure a Google Cloud project -- here's a guide you can follow:https://www.kaggle.com/nitric/google-cloud-project-setup-instructions …
Thanks for posting this! I previously tried fitting pose estimation code entirely through GCP and TF 2.3 stopped making progress on loss on TPU v GPU (although TPUs did scream through the data). Hoping this approach works around the bug (+HP tuning, yay)
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