AWS Machine Learning

MAY 31, 2023

Once configured, the Python SDK automatically inherits these values and propagates them to the underlying SageMaker API calls such as CreateProcessingJob() , CreateTrainingJob() , and CreateEndpointConfig() , with no additional actions needed. Additionally, each API call can have its own configurations.

APIs 100

APIs Scripts Accountability Enterprise 100

AWS Machine Learning

MAY 8, 2023

In this post, we address these limitations by implementing the access control outside of the MLflow server and offloading authentication and authorization tasks to Amazon API Gateway , where we implement fine-grained access control mechanisms at the resource level using Identity and Access Management (IAM). Adds an IAM authorizer.

APIs 83

APIs Accountability Scripts Management 83

AWS Machine Learning

APRIL 12, 2023

The code to invoke the pipeline script is available in the Studio notebooks, and we can change the hyperparameters and input/output when invoking the pipeline. This is quite different from our earlier method where we had all the parameters hard coded within the scripts and all the processes were inextricably linked. cpu-py39-ubuntu20.04-sagemaker",

Scripts 107

Scripts Metrics APIs Best practices 107

AWS Machine Learning

APRIL 10, 2023

In this post, we present a comprehensive guide on deploying and running inference using the Stable Diffusion inpainting model in two methods: through JumpStart’s user interface (UI) in Amazon SageMaker Studio , and programmatically through JumpStart APIs available in the SageMaker Python SDK.

Scripts 91

Scripts APIs Best practices Healthcare 91

Nexmo

AUGUST 14, 2019

And thus I thought it’d be fun to design and build something with Nexmo’s Voice and SMS APIs to do just that. Replace the API Key, API Secret, App ID, and your Nexmo Number. The post How to Create an Interactive Scavenger Hunt with Nexmo’s SMS and Voice API appeared first on Nexmo Developer Blog.

APIs 63

APIs Scripts Accountability 63

AWS Machine Learning

FEBRUARY 15, 2023

You can fine-tune and deploy JumpStart models using the UI in Amazon SageMaker Studio or using the SageMaker Python SDK extension for JumpStart APIs. This post focuses on how we can implement MLOps with JumpStart models using JumpStart APIs, Amazon SageMaker Pipelines , and Amazon SageMaker Projects. sm_client = boto3.client("sagemaker")

Scripts 113

Scripts APIs Management Enterprise 113

AWS Machine Learning

JANUARY 25, 2023

In this post, we provide an overview of how to deploy and run inference with the Stable Diffusion upscaler model in two ways: via JumpStart’s user interface (UI) in Amazon SageMaker Studio , and programmatically through JumpStart APIs available in the SageMaker Python SDK.

Scripts 85

Scripts APIs Real estate Entertainment 85

Spearline

JULY 21, 2022

And testingRTC offers multiple ways to export these metrics, from direct collection from webhooks, to downloading results in CSV format using the REST API. Flip the script With testingRTC, you only need to write scripts once, you can then run them multiple times and scale them up or down as you see fit. Happy days!

Scripts 98

Scripts Metrics APIs Analytics 98

AWS Machine Learning

MAY 5, 2023

Therefore, users without ML expertise can enjoy the benefits of a custom labels model through an API call, because a significant amount of overhead is reduced. A Python script is used to aid in the process of uploading the datasets and generating the manifest file. then((response) => { resolve(Buffer.from(response.data, "binary").toString("base64"));

Engineering 111

Engineering APIs Metrics Scripts 111

Zingtree

APRIL 14, 2015

We’re proud to announce that we’ve “officially” launched our Agent Scripting for call centers. Zingtree Interactive Decision Tree System Redefines Call Center Agent Scripting with New App. New agent scripting tools aid in training and corporate compliance for call center applications. Press release time

Scripts 48

Scripts Call Center Customer Support APIs 48

AWS Machine Learning

AUGUST 19, 2022

There are many factors you should consider to maximize CPU/GPU utilization when you run your TensorFlow script on SageMaker, such as infrastructure, type of accelerator, distributed training method, data loading method, mixed precision training, and more. SageMaker provisions the infrastructure and runs your script with MPI.

Best practices 93

Best practices APIs Scripts Advertising 93

AWS Machine Learning

JANUARY 12, 2023

Amazon API Gateway with AWS Lambda integration that converts the input text to the target language using the Amazon Translate SDK. The following steps set up API Gateway, Lambda, and Amazon Translate resources using the AWS CDK. Take note of the API key and the API endpoint created during the deployment. Prerequisites.

Customer Support 96

Customer Support APIs Scripts Enterprise 96

AWS Machine Learning

MAY 31, 2023

Triton with PyTorch backend The PyTorch backend is designed to run TorchScript models using the PyTorch C++ API. Alternatively, you can use ensemble models or business logic scripting. file in the workspace directory contains scripts to load and save a PyTorch model. client(service_name="sagemaker") runtime_sm_client = boto3.client("sagemaker-runtime")

APIs 105

APIs Scripts Accountability Best practices 105

Whitepages Pro

APRIL 4, 2019

Our latest product innovation, Transaction Risk API , was officially launched a couple of weeks ago at Merchant Risk Council (MRC) 2019. Introducing our Transaction Risk API. The Transaction Risk API was built by data scientists for data scientists and designed for easy integration into models. The new era or “Fraud 3.0”

APIs 45

APIs Scripts Customer Experience Marketing 45

AWS Machine Learning

MARCH 23, 2023

Applications and services can call the deployed endpoint directly or through a deployed serverless Amazon API Gateway architecture. To learn more about real-time endpoint architectural best practices, refer to Creating a machine learning-powered REST API with Amazon API Gateway mapping templates and Amazon SageMaker.

Scripts 124

Scripts APIs Analytics Government 124

AWS Machine Learning

OCTOBER 25, 2022

Model weights are available via scripts in the GitHub repository , and the MSAs are hosted by the Registry of Open Data on AWS (RODA). We use aws-do-eks , an open-source project that provides a large collection of easy-to-use and configurable scripts and tools to enable you to provision EKS clusters and run your inference.

Scripts 89

Scripts APIs Banking Engineering 89

AWS Machine Learning

DECEMBER 21, 2022

A new optional parameter TableFormat can be set either interactively using Amazon SageMaker Studio or through code using the API or the SDK. The following code snippet shows you how to create a feature group using the Iceberg format and FeatureGroup.create API of the SageMaker SDK. You can find the sample script in GitHub.

Scripts 86

Scripts APIs Engineering Big data 86

AWS Machine Learning

MAY 19, 2023

The DescribeForMe web app invokes the backend AI services by sending the Amazon S3 object Key in the payload to Amazon API Gateway Amazon API Gateway instantiates an AWS Step Functions workflow. A pre-signed URL with the location of the audio file stored in Amazon S3 is sent back to the user’s browser through Amazon API Gateway.

APIs 103

APIs Scripts Technology Personalization 103

AWS Machine Learning

NOVEMBER 14, 2022

You need to complete three steps to deploy your model: Create a SageMaker model: This will contain, among other parameters, the information about the model file location, the container that will be used for the deployment, and the location of the inference script. (If The inference script URI is needed in the INFERENCE_SCRIPT_S3_LOCATION.

Scripts 93

Scripts Best practices APIs Analytics 93

AWS Machine Learning

APRIL 27, 2023

Similar to the process of PyTorch integration with C++ code, Neuron CustomOps requires a C++ implementation of an operator via a NeuronCore-ported subset of the Torch C++ API. Finally, the custom library is built by calling the load API. For more information, refer to Custom Operators API Reference Guide [Experimental].

APIs 85

APIs Engineering Scripts Benchmark 85

AWS Machine Learning

NOVEMBER 7, 2022

We explore two ways of obtaining the same result: via JumpStart’s graphical interface on Amazon SageMaker Studio , and programmatically through JumpStart APIs. If you want to jump straight into the JumpStart API code we go through in this post, you can refer to the following sample Jupyter notebook: Introduction to JumpStart – Text to Image.

APIs 109

APIs Scripts Enterprise Big data 109

AWS Machine Learning

NOVEMBER 8, 2022

For example, if you’re working with a Sklearn model, you must pass in your model scripts/data within a container that properly sets up Sklearn. You can retrieve and utilize these images using the high-level SageMaker Python SDK and inject your model scripts and data into these containers. under the /code directory.

Scripts 74

Scripts APIs Best practices Management 74

AWS Machine Learning

MAY 23, 2023

The web application interacts with the models via Amazon API Gateway and AWS Lambda functions as shown in the following diagram. API Gateway provides the web application and other clients a standard RESTful interface, while shielding the Lambda functions that interface with the model. See script/sagemaker_uri.py.

APIs 116

APIs Accountability Management Technology 116

AWS Machine Learning

MAY 30, 2023

With SageMaker Processing, you can bring your own custom processing scripts and choose to build a custom container or use a SageMaker managed container with common frameworks like scikit-learn, Lime, Spark and more. Alternatively, you can use the list_processing_jobs API. You can choose from two methods to do this.

Scripts 75

Scripts Best practices Metrics APIs 75

AWS Machine Learning

MAY 25, 2023

We implement the RAG functionality inside an AWS Lambda function with Amazon API Gateway to handle routing all requests to the Lambda. We implement a chatbot application in Streamlit which invokes the function via the API Gateway and the function does a similarity search in the OpenSearch Service index for the embeddings of user question.

APIs 83

APIs Enterprise Chatbots Accountability 83

AWS Machine Learning

SEPTEMBER 28, 2022

The SageMakerMigration class consists of high-level abstractions over SageMaker APIs that significantly reduce the steps needed to deploy your model to SageMaker, as illustrated in the following figure. Prepare your trained model and inference script. pth,pkl, and so on) and an inference script.

Scripts 87

Scripts APIs Management Consulting 87

AWS Machine Learning

MAY 10, 2023

When they create a SageMaker training job, domain users can use TensorBoard using the SageMaker Python SDK or Boto3 API. Solution overview A typical training job for deep learning in SageMaker consists of two main steps: preparing a training script and configuring a SageMaker training job launcher. session.Session().region_name

Scripts 85

Scripts Metrics Management APIs 85

AWS Machine Learning

JANUARY 10, 2023

Note that the model container also includes any custom inference code or scripts that you have passed for inference. Make sure to check what container you’re using and if there are any framework-specific optimizations you can add within the script or as environment variables to inject in the container.

Best practices 90

Best practices Metrics Scripts APIs 90

AWS Machine Learning

APRIL 19, 2023

Our data scientists train the model in Python using tools like PyTorch and save the model as PyTorch scripts. Ideally, we instead want to load the model PyTorch scripts, extract the features from model input, and run model inference entirely in Java. However, a few issues came with this solution.

Scripts 87

Scripts Engineering APIs Technology 87

AWS Machine Learning

JANUARY 6, 2023

Creates an API Gateway that adds an additional layer of security between the web app user interface and Lambda. Wait until the script provisions all the required resources and finishes running. Copy the API Gateway URL that the AWS CDK script prints out and save it. (We The S3 path to the movie node file.

APIs 101

APIs Entertainment Scripts Analytics 101

AWS Machine Learning

NOVEMBER 7, 2022

We explore two ways of obtaining the same result: via JumpStart’s graphical interface on Amazon SageMaker Studio , and programmatically through JumpStart APIs. The following sections provide a step-by-step demo to perform inference, both via the Studio UI and via JumpStart APIs. JumpStart overview. Solution overview.

APIs 103

APIs Scripts Enterprise Big data 103

AWS Machine Learning

MARCH 21, 2023

Instead of hardcoding the custom function into your custom transform step, you pull a script containing the function from CodeCommit, load it, and call the loaded function in your custom transform step. We use the get_file API function to pull files from the CodeCommit repository into the Data Wrangler environment. Choose Preview.

Scripts 71

Scripts Banking Best practices APIs 71

AWS Machine Learning

JUNE 15, 2022

If you just want to read about this feature without running it yourself, you can refer to the Python script facet-search-query.py Set up the infrastructure and run the Python script to query the Amazon Kendra index. For convenience, all the steps are included in one Python script. Prerequisites. Access to AWS CloudShell.

Scripts 83

Scripts APIs Technology Management 83

AWS Machine Learning

MAY 16, 2023

As a JumpStart model hub customer, you get improved performance without having to maintain the model script outside of the SageMaker SDK. The inference script is prepacked with the model artifact. nYou can access Amazon Comprehend document analysis capabilities using the Amazon Comprehend console or using the Amazon Comprehend APIs.

Chatbots 90

Chatbots Scripts APIs Feedback 90

AWS Machine Learning

AUGUST 26, 2022

We explore two ways of obtaining the same result: via JumpStart’s graphical interface on Amazon SageMaker Studio , and programmatically through JumpStart APIs. The following sections provide a step-by-step demo to perform semantic segmentation with JumpStart, both via the Studio UI and via JumpStart APIs. Solution overview.

Scripts 90

Scripts APIs Enterprise Big data 90

AWS Machine Learning

AUGUST 18, 2022

In some ways similar to what Keras did for TensorFlow, or even arguably Hugging Face, PyTorch Lightning provides a high-level API with abstractions for much of the lower-level functionality of PyTorch itself. For PyTorch Lightning, generally speaking, there should be little-to-no code changes to simply run these APIs on SageMaker Training.

Scripts 101

Scripts APIs Benchmark Engineering 101

AWS Machine Learning

FEBRUARY 6, 2023

The JumpStart APIs allow you to programmatically deploy and fine-tune a vast selection of pre-trained models on your own datasets. These features remove the heavy lifting from each step of the ML process, making it easier to develop high-quality models and reducing time to deployment.

Metrics 84

Metrics APIs Scripts Benchmark 84