April 2018
Beginner to intermediate
500 pages
11h 26m
English
book
Hands-On Machine Learning on Google Cloud Platform
by Giuseppe Ciaburro, V Kishore Ayyadevara, Alexis Perrier, Bryan Fry, Antonio Gulli
Content preview from Hands-On Machine Learning on Google Cloud Platform
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Hyperparameter tuning in Google Cloud
In order for the just-laid-out Gaussian process to run, we have to allow our model builds to be run on Google Cloud so that hyperparameter tuning can be carried out.
In order to run hyperparameter tuning, the following are essential components:
- Data file and its location
- Model file
- Hyperparameter configuration file
- Setup file
- __init__ file
Given that we are running the model on Google Cloud ML engine, the data should be residing in a Cloud bucket so that it becomes accessible to ML engine.
This can be done by performing the following in the Cloud shell:
gsutil mb gs://my-mnist-bucketgsutil cp -r data/mnist.pkl gs://my-mnist-bucket/data/mnist.pkl
Note that, using the preceding steps, we have created ...
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