To submit a training job in Google Cloud Machine Learning (or Google Cloud AI Platform), you can use the "gcloud ai-platform jobs submit training" command. This command allows you to submit a training job to the AI Platform Training service, which provides a scalable and efficient environment for training machine learning models.
The "gcloud ai-platform jobs submit training" command requires several arguments to be specified. First, you need to provide the name of the job using the "–job-id" flag. This name should be unique within your project and can be used later to monitor the job's progress or cancel it if needed.
Next, you need to specify the training package location using the "–package-path" flag. This should point to a Python package that contains your training code and any dependencies required for the job. The package should be structured according to the guidelines provided by Google Cloud, ensuring that it can be easily deployed and executed on the AI Platform Training service.
You also need to specify the Python module name using the "–module-name" flag. This should be the name of the Python module within your package that contains the entry point for your training code. The entry point is typically a function that is responsible for configuring and executing the training process.
Additionally, you need to specify the runtime version using the "–runtime-version" flag. This determines the version of the AI Platform Training runtime that will be used to execute your training code. It's important to choose a compatible runtime version to ensure that your code runs correctly and takes advantage of any new features or improvements.
Furthermore, you can specify other optional arguments such as the job directory using the "–job-dir" flag, which is a GCS (Google Cloud Storage) location where the job's output and checkpoints will be stored. You can also specify the region using the "–region" flag to ensure that the job runs in a specific region if desired.
Here's an example command that submits a training job:
gcloud ai-platform jobs submit training my-training-job --package-path my_training_package/ --module-name my_training_module.train --runtime-version 2.4 --job-dir gs://my-bucket/my-job-dir --region us-central1
In this example, the training package is located in the "my_training_package" directory, and the entry point module is "my_training_module.train". The runtime version is set to 2.4, and the job's output will be stored in the "gs://my-bucket/my-job-dir" GCS location. The job will run in the "us-central1" region.
By using the "gcloud ai-platform jobs submit training" command with the appropriate arguments, you can easily submit a training job to the Google Cloud Machine Learning platform. This allows you to take advantage of the platform's scalability and efficiency to train your machine learning models effectively.
Other recent questions and answers regarding EITC/AI/GCML Google Cloud Machine Learning:
- What is text to speech (TTS) and how it works with AI?
- What are the limitations in working with large datasets in machine learning?
- Can machine learning do some dialogic assitance?
- What is the TensorFlow playground?
- What does a larger dataset actually mean?
- What are some examples of algorithm’s hyperparameters?
- What is ensamble learning?
- What if a chosen machine learning algorithm is not suitable and how can one make sure to select the right one?
- Does a machine learning model need supevision during its training?
- What are the key parameters used in neural network based algorithms?
View more questions and answers in EITC/AI/GCML Google Cloud Machine Learning