googleapis.com – ml

Tools (31)

Extracted live via the executor SDK.

• projects.mlProjectsExplain

  Performs explanation on the data in the request. {% dynamic include "/ai-platform/includes/_explain-request" %}

• projects.mlProjectsGetConfig

  Get the service account information associated with your project. You need this information in order to grant the service account permissions for the Google Cloud Storage location where you put your model training code for training the model with Google Cloud Machine Learning.

• projects.mlProjectsJobsCreate

  Creates a training or a batch prediction job.

• projects.mlProjectsJobsList

  Lists the jobs in the project. If there are no jobs that match the request parameters, the list request returns an empty response body: {}.

• projects.mlProjectsLocationsList

  List all locations that provides at least one type of CMLE capability.

• projects.mlProjectsLocationsStudiesCreate

  Creates a study.

• projects.mlProjectsLocationsStudiesList

  Lists all the studies in a region for an associated project.

• projects.mlProjectsLocationsStudiesTrialsAddMeasurement

  Adds a measurement of the objective metrics to a trial. This measurement is assumed to have been taken before the trial is complete.

• projects.mlProjectsLocationsStudiesTrialsCheckEarlyStoppingState

  Checks whether a trial should stop or not. Returns a long-running operation. When the operation is successful, it will contain a CheckTrialEarlyStoppingStateResponse.

• projects.mlProjectsLocationsStudiesTrialsComplete

  Marks a trial as complete.

• projects.mlProjectsLocationsStudiesTrialsCreate

  Adds a user provided trial to a study.

• projects.mlProjectsLocationsStudiesTrialsList

  Lists the trials associated with a study.

• projects.mlProjectsLocationsStudiesTrialsListOptimalTrials

  Lists the pareto-optimal trials for multi-objective study or the optimal trials for single-objective study. The definition of pareto-optimal can be checked in wiki page. https://en.wikipedia.org/wiki/Pareto_efficiency

• projects.mlProjectsLocationsStudiesTrialsStop

  Stops a trial.

• projects.mlProjectsLocationsStudiesTrialsSuggest

  Adds one or more trials to a study, with parameter values suggested by AI Platform Vizier. Returns a long-running operation associated with the generation of trial suggestions. When this long-running operation succeeds, it will contain a SuggestTrialsResponse.

• projects.mlProjectsModelsCreate

  Creates a model which will later contain one or more versions. You must add at least one version before you can request predictions from the model. Add versions by calling projects.models.versions.create.

• projects.mlProjectsModelsGetIamPolicy

  Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.

• projects.mlProjectsModelsList

  Lists the models in a project. Each project can contain multiple models, and each model can have multiple versions. If there are no models that match the request parameters, the list request returns an empty response body: {}.

• projects.mlProjectsModelsSetIamPolicy

  Sets the access control policy on the specified resource. Replaces any existing policy. Can return NOT_FOUND, INVALID_ARGUMENT, and PERMISSION_DENIED errors.

• projects.mlProjectsModelsTestIamPermissions

  Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a NOT_FOUND error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may "fail open" without warning.

• projects.mlProjectsModelsVersionsCreate

  Creates a new version of a model from a trained TensorFlow model. If the version created in the cloud by this call is the first deployed version of the specified model, it will be made the default version of the model. When you add a version to a model that already has one or more versions, the default version does not automatically change. If you want a new version to be the default, you must call projects.models.versions.setDefault.

• projects.mlProjectsModelsVersionsDelete

  Deletes a model version. Each model can have multiple versions deployed and in use at any given time. Use this method to remove a single version. Note: You cannot delete the version that is set as the default version of the model unless it is the only remaining version.

• projects.mlProjectsModelsVersionsList

  Gets basic information about all the versions of a model. If you expect that a model has many versions, or if you need to handle only a limited number of results at a time, you can request that the list be retrieved in batches (called pages). If there are no versions that match the request parameters, the list request returns an empty response body: {}.

• projects.mlProjectsModelsVersionsPatch

  Updates the specified Version resource. Currently the only update-able fields are description, requestLoggingConfig, autoScaling.minNodes, and manualScaling.nodes.

• projects.mlProjectsModelsVersionsSetDefault

  Designates a version to be the default for the model. The default version is used for prediction requests made against the model that don't specify a version. The first version to be created for a model is automatically set as the default. You must make any subsequent changes to the default version setting manually using this method.

• projects.mlProjectsOperationsCancel

  Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns google.rpc.Code.UNIMPLEMENTED. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to Code.CANCELLED.

• projects.mlProjectsOperationsGet

  Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.

• projects.mlProjectsOperationsList

  Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns UNIMPLEMENTED.

• projects.mlProjectsPredict

  Performs online prediction on the data in the request. {% dynamic include "/ai-platform/includes/_predict-request" %}

• openapi.previewSpec

  Preview an OpenAPI document before adding it as a source

• openapi.addSource

  Add an OpenAPI source and register its operations as tools