Merge branch 'master' into patch-1

doc_source/API_AddTags.md

@@ -25,7 +25,7 @@ For information about the parameters that are common to all actions, see [Common
 The request accepts the following data in JSON format\.
 
  ** [ResourceArn](#API_AddTags_RequestSyntax) **   <a name="SageMaker-AddTags-request-ResourceArn"></a>
-The Amazon Resource Name \(ARN\) of the resource that you want to tag\.   
+The Amazon Resource Name \(ARN\) of the resource that you want to tag\.  
 Type: String  
 Length Constraints: Maximum length of 256\.  
 Required: Yes
@@ -67,21 +67,12 @@ For information about the errors that are common to all actions, see [Common Err
 ## See Also<a name="API_AddTags_SeeAlso"></a>
 
 For more information about using this API in one of the language\-specific AWS SDKs, see the following:
-
 +  [AWS Command Line Interface](http://docs.aws.amazon.com/goto/aws-cli/sagemaker-2017-07-24/AddTags) 
-
 +  [AWS SDK for \.NET](http://docs.aws.amazon.com/goto/DotNetSDKV3/sagemaker-2017-07-24/AddTags) 
-
 +  [AWS SDK for C\+\+](http://docs.aws.amazon.com/goto/SdkForCpp/sagemaker-2017-07-24/AddTags) 
-
 +  [AWS SDK for Go](http://docs.aws.amazon.com/goto/SdkForGoV1/sagemaker-2017-07-24/AddTags) 
-
 +  [AWS SDK for Java](http://docs.aws.amazon.com/goto/SdkForJava/sagemaker-2017-07-24/AddTags) 
-
 +  [AWS SDK for JavaScript](http://docs.aws.amazon.com/goto/AWSJavaScriptSDK/sagemaker-2017-07-24/AddTags) 
-
 +  [AWS SDK for PHP V3](http://docs.aws.amazon.com/goto/SdkForPHPV3/sagemaker-2017-07-24/AddTags) 
-
 +  [AWS SDK for Python](http://docs.aws.amazon.com/goto/boto3/sagemaker-2017-07-24/AddTags) 
-
 +  [AWS SDK for Ruby V2](http://docs.aws.amazon.com/goto/SdkForRubyV2/sagemaker-2017-07-24/AddTags) 

doc_source/API_AlgorithmSpecification.md

@@ -2,19 +2,19 @@
 
 Specifies the training algorithm to use in a [CreateTrainingJob](http://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateTrainingJob.html) request\. 
 
-For more information about algorithms provided by Amazon SageMaker, see [Algorithms](http://docs.aws.amazon.com/sagemaker/latest/dg/algos.html)\. For information about using your own algorithms, see [Bring Your Own Algorithms ](http://docs.aws.amazon.com/sagemaker/latest/dg/adv-topics-own-algo.html)\. 
+For more information about algorithms provided by Amazon SageMaker, see [Algorithms](http://docs.aws.amazon.com/sagemaker/latest/dg/algos.html)\. For information about using your own algorithms, see [Using Your Own Algorithms with Amazon SageMaker](your-algorithms.md)\. 
 
 ## Contents<a name="API_AlgorithmSpecification_Contents"></a>
 
  **TrainingImage**   <a name="SageMaker-Type-AlgorithmSpecification-TrainingImage"></a>
-The registry path of the Docker image that contains the training algorithm\. For information about using your own algorithms, see [Docker Registry Paths for Algorithms Provided by Amazon SageMaker ](http://docs.aws.amazon.com/sagemaker/latest/dg/algos-docker-registry-paths.html)\.   
+The registry path of the Docker image that contains the training algorithm\. For information about docker registry paths for built\-in algorithms, see [Algorithms Provided by Amazon SageMaker: Common Parameters ](sagemaker-algo-docker-registry-paths.md)\.  
 Type: String  
 Length Constraints: Maximum length of 255\.  
 Required: Yes
 
  **TrainingInputMode**   <a name="SageMaker-Type-AlgorithmSpecification-TrainingInputMode"></a>
 The input mode that the algorithm supports\. For the input modes that Amazon SageMaker algorithms support, see [Algorithms](http://docs.aws.amazon.com/sagemaker/latest/dg/algos.html)\. If an algorithm supports the `File` input mode, Amazon SageMaker downloads the training data from S3 to the provisioned ML storage Volume, and mounts the directory to docker volume for training container\. If an algorithm supports the `Pipe` input mode, Amazon SageMaker streams data directly from S3 to the container\.   
- In File mode, make sure you provision ML storage volume with sufficient capacity to accomodate the data download from S3\. In addition to the training data, the ML storage volume also stores the output model\. The algorithm container use ML storage volume to also store intermediate information, if any\.   
+ In File mode, make sure you provision ML storage volume with sufficient capacity to accommodate the data download from S3\. In addition to the training data, the ML storage volume also stores the output model\. The algorithm container use ML storage volume to also store intermediate information, if any\.   
  For distributed algorithms using File mode, training data is distributed uniformly, and your training duration is predictable if the input data objects size is approximately same\. Amazon SageMaker does not split the files any further for model training\. If the object sizes are skewed, training won't be optimal as the data distribution is also skewed where one host in a training cluster is overloaded, thus becoming bottleneck in training\.   
 Type: String  
 Valid Values:` Pipe | File`   
@@ -23,11 +23,7 @@ Required: Yes
 ## See Also<a name="API_AlgorithmSpecification_SeeAlso"></a>
 
 For more information about using this API in one of the language\-specific AWS SDKs, see the following:
-
 +  [AWS SDK for C\+\+](http://docs.aws.amazon.com/goto/SdkForCpp/sagemaker-2017-07-24/AlgorithmSpecification) 
-
 +  [AWS SDK for Go](http://docs.aws.amazon.com/goto/SdkForGoV1/sagemaker-2017-07-24/AlgorithmSpecification) 
-
 +  [AWS SDK for Java](http://docs.aws.amazon.com/goto/SdkForJava/sagemaker-2017-07-24/AlgorithmSpecification) 
-
 +  [AWS SDK for Ruby V2](http://docs.aws.amazon.com/goto/SdkForRubyV2/sagemaker-2017-07-24/AlgorithmSpecification) 

doc_source/API_Channel.md

@@ -40,11 +40,7 @@ Required: No
 ## See Also<a name="API_Channel_SeeAlso"></a>
 
 For more information about using this API in one of the language\-specific AWS SDKs, see the following:
-
 +  [AWS SDK for C\+\+](http://docs.aws.amazon.com/goto/SdkForCpp/sagemaker-2017-07-24/Channel) 
-
 +  [AWS SDK for Go](http://docs.aws.amazon.com/goto/SdkForGoV1/sagemaker-2017-07-24/Channel) 
-
 +  [AWS SDK for Java](http://docs.aws.amazon.com/goto/SdkForJava/sagemaker-2017-07-24/Channel) 
-
 +  [AWS SDK for Ruby V2](http://docs.aws.amazon.com/goto/SdkForRubyV2/sagemaker-2017-07-24/Channel) 

doc_source/API_ContainerDefinition.md

@@ -36,11 +36,7 @@ Required: No
 ## See Also<a name="API_ContainerDefinition_SeeAlso"></a>
 
 For more information about using this API in one of the language\-specific AWS SDKs, see the following:
-
 +  [AWS SDK for C\+\+](http://docs.aws.amazon.com/goto/SdkForCpp/sagemaker-2017-07-24/ContainerDefinition) 
-
 +  [AWS SDK for Go](http://docs.aws.amazon.com/goto/SdkForGoV1/sagemaker-2017-07-24/ContainerDefinition) 
-
 +  [AWS SDK for Java](http://docs.aws.amazon.com/goto/SdkForJava/sagemaker-2017-07-24/ContainerDefinition) 
-
 +  [AWS SDK for Ruby V2](http://docs.aws.amazon.com/goto/SdkForRubyV2/sagemaker-2017-07-24/ContainerDefinition) 

doc_source/API_CreateEndpoint.md

@@ -84,21 +84,12 @@ HTTP Status Code: 400
 ## See Also<a name="API_CreateEndpoint_SeeAlso"></a>
 
 For more information about using this API in one of the language\-specific AWS SDKs, see the following:
-
 +  [AWS Command Line Interface](http://docs.aws.amazon.com/goto/aws-cli/sagemaker-2017-07-24/CreateEndpoint) 
-
 +  [AWS SDK for \.NET](http://docs.aws.amazon.com/goto/DotNetSDKV3/sagemaker-2017-07-24/CreateEndpoint) 
-
 +  [AWS SDK for C\+\+](http://docs.aws.amazon.com/goto/SdkForCpp/sagemaker-2017-07-24/CreateEndpoint) 
-
 +  [AWS SDK for Go](http://docs.aws.amazon.com/goto/SdkForGoV1/sagemaker-2017-07-24/CreateEndpoint) 
-
 +  [AWS SDK for Java](http://docs.aws.amazon.com/goto/SdkForJava/sagemaker-2017-07-24/CreateEndpoint) 
-
 +  [AWS SDK for JavaScript](http://docs.aws.amazon.com/goto/AWSJavaScriptSDK/sagemaker-2017-07-24/CreateEndpoint) 
-
 +  [AWS SDK for PHP V3](http://docs.aws.amazon.com/goto/SdkForPHPV3/sagemaker-2017-07-24/CreateEndpoint) 
-
 +  [AWS SDK for Python](http://docs.aws.amazon.com/goto/boto3/sagemaker-2017-07-24/CreateEndpoint) 
-
 +  [AWS SDK for Ruby V2](http://docs.aws.amazon.com/goto/SdkForRubyV2/sagemaker-2017-07-24/CreateEndpoint) 

doc_source/API_CreateEndpointConfig.md

@@ -1,6 +1,6 @@
 # CreateEndpointConfig<a name="API_CreateEndpointConfig"></a>
 
-Creates an endpoint configuration that Amazon SageMaker hosting services uses to deploy models\. In the configuration, you identify one or more models, created using the `CreateModel` API, to deploy and the resources that you want Amazon SageMaker to provision\. Then you call the [CreateEndpoint](http://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateEndpoint.html) API\. 
+Creates an endpoint configuration that Amazon SageMaker hosting services uses to deploy models\. In the configuration, you identify one or more models, created using the `CreateModel` API, to deploy and the resources that you want Amazon SageMaker to provision\. Then you call the [CreateEndpoint](http://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateEndpoint.html) API\.
 
 **Note**  
  Use this API only if you want to use Amazon SageMaker hosting services to deploy models into production\. 
@@ -94,21 +94,12 @@ HTTP Status Code: 400
 ## See Also<a name="API_CreateEndpointConfig_SeeAlso"></a>
 
 For more information about using this API in one of the language\-specific AWS SDKs, see the following:
-
 +  [AWS Command Line Interface](http://docs.aws.amazon.com/goto/aws-cli/sagemaker-2017-07-24/CreateEndpointConfig) 
-
 +  [AWS SDK for \.NET](http://docs.aws.amazon.com/goto/DotNetSDKV3/sagemaker-2017-07-24/CreateEndpointConfig) 
-
 +  [AWS SDK for C\+\+](http://docs.aws.amazon.com/goto/SdkForCpp/sagemaker-2017-07-24/CreateEndpointConfig) 
-
 +  [AWS SDK for Go](http://docs.aws.amazon.com/goto/SdkForGoV1/sagemaker-2017-07-24/CreateEndpointConfig) 
-
 +  [AWS SDK for Java](http://docs.aws.amazon.com/goto/SdkForJava/sagemaker-2017-07-24/CreateEndpointConfig) 
-
 +  [AWS SDK for JavaScript](http://docs.aws.amazon.com/goto/AWSJavaScriptSDK/sagemaker-2017-07-24/CreateEndpointConfig) 
-
 +  [AWS SDK for PHP V3](http://docs.aws.amazon.com/goto/SdkForPHPV3/sagemaker-2017-07-24/CreateEndpointConfig) 
-
 +  [AWS SDK for Python](http://docs.aws.amazon.com/goto/boto3/sagemaker-2017-07-24/CreateEndpointConfig) 
-
 +  [AWS SDK for Ruby V2](http://docs.aws.amazon.com/goto/SdkForRubyV2/sagemaker-2017-07-24/CreateEndpointConfig) 

doc_source/API_CreateModel.md

@@ -29,7 +29,11 @@ In the request, you also provide an IAM role that Amazon SageMaker can assume to
          "[Key](API_Tag.md#SageMaker-Type-Tag-Key)": "string",
          "[Value](API_Tag.md#SageMaker-Type-Tag-Value)": "string"
       }
-   ]
+   ],
+   "[VpcConfig](#SageMaker-CreateModel-request-VpcConfig)": { 
+      "[SecurityGroupIds](API_VpcConfig.md#SageMaker-Type-VpcConfig-SecurityGroupIds)": [ "string" ],
+      "[Subnets](API_VpcConfig.md#SageMaker-Type-VpcConfig-Subnets)": [ "string" ]
+   }
 }
 ```
 
@@ -62,6 +66,11 @@ Required: Yes
 An array of key\-value pairs\. For more information, see [Using Cost Allocation Tags](http://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what) in the *AWS Billing and Cost Management User Guide*\.   
 Type: Array of [Tag](API_Tag.md) objects  
 Array Members: Minimum number of 0 items\. Maximum number of 50 items\.  
+Required: No
+
+ ** [VpcConfig](#API_CreateModel_RequestSyntax) **   <a name="SageMaker-CreateModel-request-VpcConfig"></a>
+A [VpcConfig](API_VpcConfig.md) object that specifies the VPC that you want your model to connect to\. Control access to and from your training container by configuring the VPC\. For more information, see [Protect Models by Using an Amazon Virtual Private Cloud](host-vpc.md)\.  
+Type: [VpcConfig](API_VpcConfig.md) object  
 Required: No
 
 ## Response Syntax<a name="API_CreateModel_ResponseSyntax"></a>
@@ -94,21 +103,12 @@ HTTP Status Code: 400
 ## See Also<a name="API_CreateModel_SeeAlso"></a>
 
 For more information about using this API in one of the language\-specific AWS SDKs, see the following:
-
 +  [AWS Command Line Interface](http://docs.aws.amazon.com/goto/aws-cli/sagemaker-2017-07-24/CreateModel) 
-
 +  [AWS SDK for \.NET](http://docs.aws.amazon.com/goto/DotNetSDKV3/sagemaker-2017-07-24/CreateModel) 
-
 +  [AWS SDK for C\+\+](http://docs.aws.amazon.com/goto/SdkForCpp/sagemaker-2017-07-24/CreateModel) 
-
 +  [AWS SDK for Go](http://docs.aws.amazon.com/goto/SdkForGoV1/sagemaker-2017-07-24/CreateModel) 
-
 +  [AWS SDK for Java](http://docs.aws.amazon.com/goto/SdkForJava/sagemaker-2017-07-24/CreateModel) 
-
 +  [AWS SDK for JavaScript](http://docs.aws.amazon.com/goto/AWSJavaScriptSDK/sagemaker-2017-07-24/CreateModel) 
-
 +  [AWS SDK for PHP V3](http://docs.aws.amazon.com/goto/SdkForPHPV3/sagemaker-2017-07-24/CreateModel) 
-
 +  [AWS SDK for Python](http://docs.aws.amazon.com/goto/boto3/sagemaker-2017-07-24/CreateModel) 
-
 +  [AWS SDK for Ruby V2](http://docs.aws.amazon.com/goto/SdkForRubyV2/sagemaker-2017-07-24/CreateModel) 

doc_source/API_CreateNotebookInstance.md

@@ -1,16 +1,16 @@
 # CreateNotebookInstance<a name="API_CreateNotebookInstance"></a>
 
-Creates an Amazon SageMaker notebook instance\. A notebook instance is an ML compute instance running on a Jupyter notebook\. 
+Creates an Amazon SageMaker notebook instance\. A notebook instance is a machine learning \(ML\) compute instance running on a Jupyter notebook\. 
 
-In a `CreateNotebookInstance` request, you specify the type of ML compute instance that you want to run\. Amazon SageMaker launches the instance, installs common libraries that you can use to explore datasets for model training, and attaches an ML storage volume to the notebook instance\. 
+In a `CreateNotebookInstance` request, specify the type of ML compute instance that you want to run\. Amazon SageMaker launches the instance, installs common libraries that you can use to explore datasets for model training, and attaches an ML storage volume to the notebook instance\. 
 
-Amazon SageMaker also provides a set of example notebooks\. Each notebook demonstrates how to use Amazon SageMaker with a specific an algorithm or with a machine learning framework\. 
+Amazon SageMaker also provides a set of example notebooks\. Each notebook demonstrates how to use Amazon SageMaker with a specific algorithm or with a machine learning framework\. 
 
 After receiving the request, Amazon SageMaker does the following:
 
 1. Creates a network interface in the Amazon SageMaker VPC\.
 
-1. \(Option\) If you specified `SubnetId`, creates a network interface in your own VPC, which is inferred from the subnet ID that you provide in the input\. When creating this network interface, Amazon SageMaker attaches the security group that you specified in the request to the network interface that it creates in your VPC\.
+1. \(Option\) If you specified `SubnetId`, Amazon SageMaker creates a network interface in your own VPC, which is inferred from the subnet ID that you provide in the input\. When creating this network interface, Amazon SageMaker attaches the security group that you specified in the request to the network interface that it creates in your VPC\.
 
 1. Launches an EC2 instance of the type specified in the request in the Amazon SageMaker VPC\. If you specified `SubnetId` of your VPC, Amazon SageMaker specifies both network interfaces when launching this instance\. This enables inbound traffic from your own VPC to the notebook instance, assuming that the security groups allow it\.
 
@@ -24,8 +24,10 @@ For more information, see [How It Works](http://docs.aws.amazon.com/sagemaker/la
 
 ```
 {
+   "[DirectInternetAccess](#SageMaker-CreateNotebookInstance-request-DirectInternetAccess)": "string",
    "[InstanceType](#SageMaker-CreateNotebookInstance-request-InstanceType)": "string",
    "[KmsKeyId](#SageMaker-CreateNotebookInstance-request-KmsKeyId)": "string",
+   "[LifecycleConfigName](#SageMaker-CreateNotebookInstance-request-LifecycleConfigName)": "string",
    "[NotebookInstanceName](#SageMaker-CreateNotebookInstance-request-NotebookInstanceName)": "string",
    "[RoleArn](#SageMaker-CreateNotebookInstance-request-RoleArn)": "string",
    "[SecurityGroupIds](#SageMaker-CreateNotebookInstance-request-SecurityGroupIds)": [ "string" ],
@@ -45,16 +47,30 @@ For information about the parameters that are common to all actions, see [Common
 
 The request accepts the following data in JSON format\.
 
+ ** [DirectInternetAccess](#API_CreateNotebookInstance_RequestSyntax) **   <a name="SageMaker-CreateNotebookInstance-request-DirectInternetAccess"></a>
+Sets whether Amazon SageMaker provides internet access to the notebook instance\. If you set this to `Disabled` this notebook instance will be able to access resources only in your VPC, and will not be able to connect to Amazon SageMaker training and endpoint services unless your configure a NAT Gateway in your VPC\.  
+For more information, see [Notebook Instances Are Enabled with Internet Access by Default](appendix-additional-considerations.md#appendix-notebook-and-internet-access)\. You can set the value of this parameter to `Disabled` only if you set a value for the `SubnetId` parameter\.  
+Type: String  
+Valid Values:` Enabled | Disabled`   
+Required: No
+
  ** [InstanceType](#API_CreateNotebookInstance_RequestSyntax) **   <a name="SageMaker-CreateNotebookInstance-request-InstanceType"></a>
 The type of ML compute instance to launch for the notebook instance\.  
 Type: String  
-Valid Values:` ml.t2.medium | ml.m4.xlarge | ml.p2.xlarge | ml.p3.2xlarge`   
+Valid Values:` ml.t2.medium | ml.t2.large | ml.t2.xlarge | ml.t2.2xlarge | ml.m4.xlarge | ml.m4.2xlarge | ml.m4.4xlarge | ml.m4.10xlarge | ml.m4.16xlarge | ml.p2.xlarge | ml.p2.8xlarge | ml.p2.16xlarge | ml.p3.2xlarge | ml.p3.8xlarge | ml.p3.16xlarge`   
 Required: Yes
 
  ** [KmsKeyId](#API_CreateNotebookInstance_RequestSyntax) **   <a name="SageMaker-CreateNotebookInstance-request-KmsKeyId"></a>
  If you provide a AWS KMS key ID, Amazon SageMaker uses it to encrypt data at rest on the ML storage volume that is attached to your notebook instance\.   
 Type: String  
 Length Constraints: Maximum length of 2048\.  
+Required: No
+
+ ** [LifecycleConfigName](#API_CreateNotebookInstance_RequestSyntax) **   <a name="SageMaker-CreateNotebookInstance-request-LifecycleConfigName"></a>
+The name of a lifecycle configuration to associate with the notebook instance\. For information about lifestyle configurations, see [Step 2\.1: \(Optional\) Customize a Notebook Instance ](notebook-lifecycle-config.md)\.  
+Type: String  
+Length Constraints: Maximum length of 63\.  
+Pattern: `^[a-zA-Z0-9](-*[a-zA-Z0-9])*`   
 Required: No
 
  ** [NotebookInstanceName](#API_CreateNotebookInstance_RequestSyntax) **   <a name="SageMaker-CreateNotebookInstance-request-NotebookInstanceName"></a>
@@ -120,21 +136,12 @@ HTTP Status Code: 400
 ## See Also<a name="API_CreateNotebookInstance_SeeAlso"></a>
 
 For more information about using this API in one of the language\-specific AWS SDKs, see the following:
-
 +  [AWS Command Line Interface](http://docs.aws.amazon.com/goto/aws-cli/sagemaker-2017-07-24/CreateNotebookInstance) 
-
 +  [AWS SDK for \.NET](http://docs.aws.amazon.com/goto/DotNetSDKV3/sagemaker-2017-07-24/CreateNotebookInstance) 
-
 +  [AWS SDK for C\+\+](http://docs.aws.amazon.com/goto/SdkForCpp/sagemaker-2017-07-24/CreateNotebookInstance) 
-
 +  [AWS SDK for Go](http://docs.aws.amazon.com/goto/SdkForGoV1/sagemaker-2017-07-24/CreateNotebookInstance) 
-
 +  [AWS SDK for Java](http://docs.aws.amazon.com/goto/SdkForJava/sagemaker-2017-07-24/CreateNotebookInstance) 
-
 +  [AWS SDK for JavaScript](http://docs.aws.amazon.com/goto/AWSJavaScriptSDK/sagemaker-2017-07-24/CreateNotebookInstance) 
-
 +  [AWS SDK for PHP V3](http://docs.aws.amazon.com/goto/SdkForPHPV3/sagemaker-2017-07-24/CreateNotebookInstance) 
-
 +  [AWS SDK for Python](http://docs.aws.amazon.com/goto/boto3/sagemaker-2017-07-24/CreateNotebookInstance) 
-
 +  [AWS SDK for Ruby V2](http://docs.aws.amazon.com/goto/SdkForRubyV2/sagemaker-2017-07-24/CreateNotebookInstance)