Learn how to run training in Cloud ML synchronously using the command line.
- [Instructor] Let's use the shell command line…to run ML training synchronously in the local mode.…We do so by using the following command:…gcloud ml-engine local train,…the package-path to the package we created,…and the module-name under the package that needs to be run.…Let's run through the code to see what it means.…We will use the gcloud utility.…We specify the ml-engine as the subset of commands to use.…
Local specifies that it is run on the local VM.…Train specifies the command.…The package option specifies the location…where the code for this exercise exists.…The module-name specifies the name of the module…that needs to be run.…In this case, it is just the file name.…Note that when run, this will access the data…available in cloud storage.…It will also save the module back into cloud storage.…Let's run the command now.…
The command will execute the propensity-cloud.by file.…It will download the CSV file, build the model,…and upload the model back into cloud storage.…It is also printing all the messages to the console.…
- Evaluating the machine learning tools in GCP
- Understanding the predictive analytics process
- Building models
- Training models with jobs
- Building and running predictions
- Best practices for cost control, testing, and performance monitoring
Skill Level Intermediate
Predictive Customer Analyticswith Kumaran Ponnambalam1h 37m Intermediate
1. ML Options in GCP
2. Cloud ML Basics
3. Model Building with Cloud ML
4. Predictions in Cloud ML
5. Cloud ML Best Practices
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