training pipeline

Related topics

• training pipeline depends on dataset From the official documentation: “When you have a dataset with a representative set of training items, you are ready to create an AutoML Edge training pipeline.”
• BigQuery works with training pipeline From the official documentation: “If you use a managed dataset in an Agent Platform training pipeline that utilizes Ray for distributed training, the data from the managed dataset is made available to the training containers, which your Ray application can then access (via mounted Cloud Storage or BigQuery if…”
• Hyperparameter tuning job is part of training pipeline From the official documentation: “This training pipeline encapsulates a hyperparameter tuning job with an added convenience step that makes it easier to deploy your model to Agent Platform after training.”
• Managed dataset works with training pipeline From the official documentation: “If you use a managed dataset in an Agent Platform training pipeline that utilizes Ray for distributed training, the data from the managed dataset is made available to the training containers, which your Ray application can then access (via mounted Cloud Storage or BigQuery if…”
• model is part of training pipeline From the official documentation: “TrainingPipeline trainingPipeline = TrainingPipeline.newBuilder() .setDisplayName(displayName) .setInputDataConfig(inputDataConfig) .setTrainingTaskDefinition(customTaskDefinition) .setTrainingTaskInputs(trainingTaskInputs) .setModelToUpload(model) .build();”
• training pipeline is part of Agent Platform From the official documentation: “This section describes using the training package that you uploaded to Cloud Storage to run an Agent Platform custom training pipeline.”
• training pipeline is part of Gemini Enterprise Agent Platform From the official documentation: “There are three types of Agent Platform resources you can create to train custom models on Agent Platform: - [Custom jobs](/gemini-enterprise-agent-platform/machine-learning/training/create-custom-job) - [Hyperparameter tuning…”
• training pipeline depends on Google Cloud Storage From the official documentation: “This section describes using the training package that you uploaded to Cloud Storage to run an Agent Platform custom training pipeline.”
• BigQuery works with Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
• VPC Service Controls secures BigQuery From the official documentation: “BigQuery data is protected with VPC Service Controls”
• BigQuery is an alternative to Google Cloud Storage From the official documentation: “The training data can be either a CSV file in Cloud Storage or a table in BigQuery.”
• BigQuery works with Spanner From the official documentation: “Federated analytics seamlessly combine data from Spanner and other sources in BigQuery.”
• BigQuery works with Gemini Enterprise Agent Platform From the official documentation: “The BigQuery dataset stores all versions for the associated Gemini Enterprise Agent Platform dataset.”
• VPC Service Controls secures Gemini Enterprise Agent Platform From the official documentation: “The VPC Service Controls service perimeter blocks access from Agent Platform to third-party APIs and services on the internet.”
• Cloud Audit Logs works with VPC Service Controls From the official documentation: “VPC Service Controls integrate with Cloud Audit Logs to monitor access to the control plane.”
• customer-managed encryption keys secures BigQuery From the official documentation: “You can either create CMEKs manually to protect your BigQuery resources or use Cloud KMS Autokey.”
• BigQuery works with Cloud Audit Logs From the official documentation: “Cloud Audit Logs maintain a record of Google Cloud events, including BigQuery events.”
• BigQuery works with Google Cloud Storage From the official documentation: “Load Cloud Storage data into BigQuery”
• Cloud Logging works with Gemini Enterprise Agent Platform From the official documentation: “When you run a training job, Gemini Enterprise Agent Platform training saves logs to [Logging](/logging/docs).”
• customer-managed encryption keys secures Gemini Enterprise Agent Platform From the official documentation: “Enable customer-managed encryption keys (CMEK) for the Gemini Enterprise Agent Platform to gain more control over data encryption and key management.”
• Identity and Access Management secures Spanner From the official documentation: “Identity and Access Management (IAM) lets you control user and group access to Spanner resources at the project, Spanner instance, and Spanner database levels.”
• Agent Platform works with Spanner From the official documentation: “If both the Spanner database and the Agent Platform endpoint are in the same project, then no additional setup is required.”
• BigQuery depends on Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
• BigQuery works with Identity and Access Management From the official documentation: “BigQuery uses Identity and Access Management (IAM) for authorization.”
• Cloud Audit Logs works with Cloud Logging From the official documentation: “- For real-time analysis, alerting, and visualization, stream the audit logs to [Logging](/logging/docs/overview).”
• Cloud Logging works with customer-managed encryption keys From the official documentation: “To use Cloud Logging with Customer-managed encryption keys (CMEK), you must complete the steps in the [Enable CMEK for an organization](/logging/docs/routing/managed-encryption#enable) page in the Cloud Logging documentation.”
• Cloud Logging works with Google Cloud Storage From the official documentation: “Cloud Logging can [route logs](/logging/docs/export/configure_export_v2) to Cloud Storage by Google SecOps on a scheduled basis.”
• Cloud Logging is an alternative to Google Cloud Storage From the official documentation: “When you specify your own service account for builds, you must store your build logs in a Cloud Logging bucket, in a user-created Cloud Storage bucket, or in a Google Cloud-created and user-owned Cloud Storage bucket.”
• customer-managed encryption keys configures Cloud Logging From the official documentation: “To use Cloud Logging with Customer-managed encryption keys (CMEK), you must complete the steps in the [Enable CMEK for an organization](/logging/docs/routing/managed-encryption#enable) page in the Cloud Logging documentation.”
• customer-managed encryption keys secures dataset From the official documentation: “For **datasets**, when a user imports data into dataset, the data items and annotations are CMEK-encrypted.”
• Google Cloud Storage works with Spanner From the official documentation: “- Export any Spanner database into a Cloud Storage bucket using either Avro or CSV file formats.”
• Identity and Access Management works with VPC Service Controls From the official documentation: “VPC Service Controls perimeters and Identity and Access Management (IAM) roles work together.”
• Agent Platform works with BigQuery From the official documentation: “BigQuery and Agent Platform are tightly integrated, letting you access and analyze your data directly within the Agent Platform platform.”
• Agent Platform works with Cloud Logging From the official documentation: “If any containers restart before Agent Platform shuts down the entire job, these containers may produce logs in Cloud Logging.”
• Agent Platform depends on dataset From the official documentation: “The Agent Platform API uses the items from the dataset to train the model, test it, and evaluate model performance.”
• Agent Platform works with VPC Service Controls From the official documentation: “Agent Platform supports Google Cloud security controls that you can use to meet your requirements for data residency, [customer-managed encryption keys (CMEK)](/gemini-enterprise-agent-platform/machine-learning/general/cmek), network security using [VPC Service…”
• BigQuery works with VPC Service Controls From the official documentation: “BigQuery integrates with VPC Service Controls to restrict access to your BigQuery resources from specific networks.”
• Cloud Audit Logs secures BigQuery From the official documentation: “For BigQuery, [Cloud Audit Logs](/logging/docs/audit) is used for both data access logs and audit logs, which are enabled by default.”
• Cloud Audit Logs works with dataset From the official documentation: “Check whether the table or dataset expired or was deleted by querying [`INFORMATION_SCHEMA.TABLE_STORAGE`](/bigquery/docs/information-schema-table-storage) or inspecting Cloud Audit Logs for `DeleteTable` or `InternalTableExpired` events.”
• Cloud Audit Logs secures Gemini Enterprise Agent Platform From the official documentation: “You can use Cloud Audit Logs to track changes to Identity and Access Management policies for your Agent Platform resources.”
• Cloud Audit Logs works with Google Cloud Storage From the official documentation: “The sample code shows you how to read Cloud Storage events using Cloud Audit Logs in a service deployed to Cloud Run.”
• Cloud Logging depends on customer-managed encryption keys From the official documentation: “To use Cloud Logging with Customer-managed encryption keys (CMEK), you must complete the steps in the [Enable CMEK for an organization](/logging/docs/routing/managed-encryption#enable) page in the Cloud Logging documentation.”
• Cloud Logging works with Spanner From the official documentation: “Both Spanner and Agent Platform provide monitoring dashboards and write logs to Cloud Logging, which can contain additional details.”
• Cloud Logging works with VPC Service Controls From the official documentation: “This page describes how you can find VPC Service Controls errors using Cloud Logging.”
• customer-managed encryption keys is part of BigQuery From the official documentation: “If you require more control over encryption keys, BigQuery supports [customer-managed encryption keys](/bigquery/docs/customer-managed-encryption) in the [Cloud Key Management Service](/kms/docs).”
• customer-managed encryption keys secures Cloud Logging From the official documentation: “To use Cloud Logging with Customer-managed encryption keys (CMEK), you must complete the steps in the [Enable CMEK for an organization](/logging/docs/routing/managed-encryption#enable) page in the Cloud Logging documentation.”
• customer-managed encryption keys secures Google Cloud Storage From the official documentation: “In IL5, CMEK is enabled by default for Compute Engine, Google Kubernetes Engine (GKE), Cloud Storage, and Cloud SQL.”
• customer-managed encryption keys secures model From the official documentation: “For **models**, the models stored in the storage system (for example, disk) are CMEK-encrypted.”
• customer-managed encryption keys works with Spanner From the official documentation: “`SPANNER_PROJECT` - A Google Cloud project that contains a Spanner instance which uses the customer-managed encryption keys (CMEKs) that reside in `KEY_PROJECT`.”
• customer-managed encryption keys secures Spanner From the official documentation: “To learn how to use manually-created CMEKs to protect your Spanner resources, see [Secure a database with CMEK](/spanner/docs/use-cmek).”
• dataset is part of Agent Platform From the official documentation: “This page shows you how to create an Agent Platform dataset from your image data so you can start training classification models.”
• dataset is part of BigQuery From the official documentation: “Create a BigQuery dataset to store your models and sample data:”
• dataset is part of Gemini Enterprise Agent Platform From the official documentation: “This resource always executes the training task, and optionally may also export data from a Gemini Enterprise Agent Platform `Dataset` which becomes the training input, upload the Model to Gemini Enterprise Agent Platform, and evaluate the Model.”
• dataset depends on Google Cloud Storage From the official documentation: “Create a dataset using an empty Cloud Storage bucket.”
• Gemini Enterprise Agent Platform depends on Identity and Access Management From the official documentation: “Agent Platform uses IAM to manage access to resources.”
• Gemini Enterprise Agent Platform works with Identity and Access Management From the official documentation: “Learn more about [Gemini Enterprise Agent Platform access control with IAM](/gemini-enterprise-agent-platform/machine-learning/general/access-control).”
• Gemini Enterprise Agent Platform works with Spanner From the official documentation: “MODEL DDL statements and ML functions in Spanner invoke Gemini Enterprise Agent Platform endpoints and can fail due to various reasons:”
• Hyperparameter tuning job is part of Gemini Enterprise Agent Platform From the official documentation: “There are three types of Agent Platform resources you can create to train custom models on Agent Platform: - [Custom jobs](/gemini-enterprise-agent-platform/machine-learning/training/create-custom-job) - [Hyperparameter tuning…”
• Identity and Access Management secures Agent Platform From the official documentation: “Agent Platform uses Identity and Access Management (IAM) for authorization.”
• Identity and Access Management secures BigQuery From the official documentation: “Security in BigQuery is intrinsically linked to [Identity and Access Management (IAM)](/iam/docs/overview) in Google Cloud.”