AWS Machine Learning

MAY 30, 2024

AWS Prototyping successfully delivered a scalable prototype, which solved CBRE’s business problem with a high accuracy rate (over 95%) and supported reuse of embeddings for similar NLQs, and an API gateway for integration into CBRE’s dashboards. The following diagram illustrates the web interface and API management layer.

Real estate 124

Real estate APIs Metrics Construction 124

AWS Machine Learning

JUNE 12, 2024

This solution uses an Amazon Cognito user pool as an OAuth-compatible identity provider (IdP), which is required in order to exchange a token with AWS IAM Identity Center and later on interact with the Amazon Q Business APIs. Amazon Q uses the chat_sync API to carry out the conversation. You can also find the script on the GitHub repo.

APIs 128

APIs Enterprise Accountability Feedback 128

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 98

APIs Scripts Enterprise Big data 98

Kunnect

APRIL 28, 2015

We’re excited to announce that we’ve completed an integration using the Salesforce.com application programming interface (API). Contact us for a free demo. At Kunnect, we’re constantly looking for ways to make our cloud-based call center software even more convenient and user-friendly. Why is this important?

APIs 48

APIs call center software CRM Call Center 48

AWS Machine Learning

FEBRUARY 29, 2024

The Retrieve and RetrieveAndGenerate APIs allow your applications to directly query the index using a unified and standard syntax without having to learn separate APIs for each different vector database, reducing the need to write custom index queries against your vector store.

APIs 131

APIs Healthcare Scripts Enterprise 131

AWS Machine Learning

AUGUST 30, 2023

pre_trained_model = Model( image_uri=deploy_image_uri, model_data=pre_trained_model_uri, role=aws_role, predictor_cls=Predictor, name=pre_trained_name, env=large_model_env, ) # Deploy the pre-trained model.

Healthcare 130

Healthcare APIs Scripts Metrics 130

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 92

APIs Scripts Enterprise Big data 92

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. The following examples contain code snippets.

Scripts 84

Scripts APIs Real estate Entertainment 84

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.

APIs 89

APIs Scripts Enterprise Big data 89

AWS Machine Learning

NOVEMBER 22, 2023

Amazon Bedrock is a fully managed service that offers an easy-to-use API for accessing foundation models for text, image, and embedding. Amazon Location offers an API for maps, places, and routing with data provided by trusted third parties such as Esri, HERE, Grab, and OpenStreetMap.

APIs 112

APIs Scripts Engineering Accountability 112

AWS Machine Learning

DECEMBER 22, 2023

Amazon Bedrock is a fully managed service that makes leading FMs from AI companies available through an API along with developer tooling to help build and scale generative AI applications. Solution Deployment Automation Script The preceding source./create-stack.sh The agent is equipped with tools that include an Anthropic Claude 2.1

Scripts 118

Scripts Chatbots Accountability Multi-channel support 118

AWS Machine Learning

NOVEMBER 14, 2022

We provide a step-by-step guide to deploy your SageMaker trained model to Graviton-based instances, cover best practices when working with Graviton, discuss the price-performance benefits, and demo how to deploy a TensorFlow model on a SageMaker Graviton instance. The inference script is stored in Amazon Simple Storage Service (Amazon S3).

Scripts 92

Scripts APIs Best practices Engineering 92

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 90

Scripts APIs Construction Finance 90

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. Clone and set up the AWS CDK application.

APIs 105

APIs Accountability Construction Management 105

AWS Machine Learning

JULY 14, 2022

It runs on all major operating systems (Linux, macOS, and Windows), and works independently of the programming languages (Python, R, Julia, shell scripts, and so on) or ML libraries (Keras, TensorFlow, PyTorch, Scipy, and more) used in the project. In the file browser, choose the amazon-sagemaker-experiments-dvc-demo repository.

Scripts 91

Scripts Engineering Metrics APIs 91

AWS Machine Learning

JULY 26, 2023

We compile the UNet for one batch (by using input tensors with one batch), then use the torch_neuronx.DataParallel API to load this single batch model onto each core. Load the UNet model onto two Neuron cores using the torch_neuronx.DataParallel API. If you have a custom inference script, you need to provide that instead.

Scripts 91

Scripts APIs Benchmark Engineering 91

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.

Engineering 86

Engineering APIs Scripts Education 86

AWS Machine Learning

NOVEMBER 1, 2022

Autopilot training jobs start their own dedicated SageMaker backend processes, and dedicated SageMaker API calls are required to start new training jobs, monitor training job statuses, and invoke trained Autopilot models. We use a Lambda step because the API call to Autopilot is lightweight. script creates an Autopilot job.

Scripts 90

Scripts APIs Metrics Engineering 90

AWS Machine Learning

SEPTEMBER 1, 2023

We use Streamlit for the sample demo application UI. Solution overview To get responses streamed back from SageMaker, you can use our new InvokeEndpointWithResponseStream API. To take advantage of the new streaming API, you need to make sure the model container returns the streamed response as chunked encoded data.

APIs 108

APIs Chatbots Engineering Best practices 108

AWS Machine Learning

NOVEMBER 17, 2022

In this post, we provide an overview of how to deploy and run inference with the AlexaTM 20B model programmatically through JumpStart APIs, available in the SageMaker Python SDK. The following sections provide a step-by-step demo on how to deploy the model, run inference, and do in-context-learning to solve few-shot learning tasks.

Scripts 101

Scripts APIs Government Engineering 101

AWS Machine Learning

FEBRUARY 20, 2023

In this post, we provide an overview of how to fine-tune the Stable Diffusion model in two ways: programmatically through JumpStart APIs available in the SageMaker Python SDK , and JumpStart’s user interface (UI) in Amazon SageMaker Studio. Fine-tuning large models like Stable Diffusion usually requires you to provide training scripts.

Scripts 92

Scripts APIs Entertainment Construction 92

AWS Machine Learning

JUNE 28, 2023

Solution overview Amazon Rekognition and Amazon Comprehend are managed AI services that provide pre-trained and customizable ML models via an API interface, eliminating the need for machine learning (ML) expertise. The RESTful API will return the generated image and the moderation warnings to the client if unsafe information is detected.

APIs 95

APIs Advertising Engineering Construction 95

AWS Machine Learning

AUGUST 17, 2023

Deploy the CloudFormation template Complete the following steps to deploy the CloudFormation template: Save the CloudFormation template sm-redshift-demo-vpc-cfn-v1.yaml Enter a stack name, such as Demo-Redshift. You should see a new CloudFormation stack with the name Demo-Redshift being created. yaml locally.

APIs 85

APIs Engineering Scripts Analytics 85

AWS Machine Learning

NOVEMBER 25, 2022

When our tuning job is complete, we look at some of the methods available to explore the results, both via the AWS Management Console and programmatically via the AWS SDKs and APIs. We use the XGBoost algorithm, one of many algorithms provided as a SageMaker built-in algorithm (no training script required!).

Scripts 87

Scripts APIs Metrics Construction 87

AWS Machine Learning

MAY 17, 2023

The events trigger Lambda functions to make API calls to Amazon Transcribe and invoke the real-time endpoint hosting the Flan T5 XL model. Once created, the endpoint can be invoked with the InvokeEndpoint API. When the status is Complete , return to the Amazon S3 console and open the demo bucket. Choose Create folder.

APIs 82

APIs Scripts Engineering Management 82

AWS Machine Learning

MAY 22, 2023

job name: jumpstart-demo-xl-3-2023-04-06-08-16-42-738 INFO:sagemaker:Creating training-job with name: jumpstart-demo-xl-3-2023-04-06-08-16-42-738 When the training is complete, you have a fine-tuned model at model_uri. Let’s use it!

APIs 106

APIs Scripts Metrics Accountability 106

Balto

JANUARY 6, 2025

Get a free demo now and explore it in action! Dynamic Prompts: Assist your agents during make-or-break moments with timely responses and questions to improve their performance and improve customer satisfaction. Seamlessly integrate Balto into your systems and maintain a cohesive tool arsenal that propels your call center forward.

Call Center 52

Call Center Coaching Surveys Contact Center 52

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. A short demo to showcase the JumpStartOpenChatKitShell is shown in the following video. The deploy method may take a few minutes.

Chatbots 94

Chatbots Scripts APIs Feedback 94

AWS Machine Learning

JUNE 9, 2022

Recently, we also announced the launch of easy-to-use JumpStart APIs as an extension of the SageMaker Python SDK, allowing you to programmatically deploy and fine-tune a vast selection of JumpStart-supported pre-trained models on your own datasets. JumpStart overview. This dataset comprises images of five types of flowers.

Scripts 76

Scripts APIs Enterprise Accountability 76

AWS Machine Learning

JUNE 10, 2022

Generally speaking, the SDK for JavaScript provides access to AWS services in either browser scripts or Node.js; for this sample project, the SDK is used in browser scripts. For additional information about how to access AWS services from a browser script, refer to Getting Started in a Browser Script. About the Author.

Scripts 86

Scripts APIs Accountability Engineering 86

AWS Machine Learning

NOVEMBER 21, 2022

Now we can take a closer look at some of the assets that are included in this solution, starting with the demo notebook. Demo notebook. You can use the demo notebook to send example data to already deployed model endpoints for the document summarization and question answering tasks. Text classification.

Scripts 83

Scripts Metrics APIs Healthcare 83

AWS Machine Learning

MARCH 20, 2023

Use the supplied Python scripts for quantization. Run the provided Python test scripts to invoke the SageMaker endpoint for both INT8 and FP32 versions. Quantizing the model in PyTorch is possible with a few APIs from Intel PyTorch extensions. py scripts for testing. times greater with INT8 quantization.

Calibration 89

Calibration Scripts Benchmark APIs 89

AWS Machine Learning

OCTOBER 11, 2022

It provides APIs powered by ML to extract key phrases, entities, sentiment analysis, and more. For this demo, you should have the following prerequisites: An AWS account. To install the active LTS version of Node.js, you can use the following install script for nvm and use nvm to install the Node.js Prerequisites. LTS version.

APIs 88

APIs Enterprise Engineering Accountability 88

AWS Machine Learning

DECEMBER 6, 2023

Another driver behind RAG’s popularity is its ease of implementation and the existence of mature vector search solutions, such as those offered by Amazon Kendra (see Amazon Kendra launches Retrieval API ) and Amazon OpenSearch Service (see k-Nearest Neighbor (k-NN) search in Amazon OpenSearch Service ), among others.

Analytics 121

Analytics APIs Engineering Construction 121

AWS Machine Learning

JANUARY 19, 2024

In this demo, the target task is a binary classification problem where BERT is used to identify, from a dataset that consists of a collection of pairs of text fragments, whether the meaning of one text fragment can be inferred from the other fragment. training.py ). First, we import the necessary Locust and Boto3 libraries.

Metrics 116

Metrics Scripts Benchmark Enterprise 116

CSM Magazine

SEPTEMBER 21, 2023

The upgrade integrates an array of powerful technologies, including CRM, workforce optimisation and enhanced omnichannel features like outbound dialler, drag-and-drop IVR and workflow builder and agent scripting. Book a demo here. The future of contact centre customer service is here, and its powered by Cirrus.

APIs 59

APIs Scripts Interactive Voice Response CRM 59

AWS Machine Learning

JUNE 20, 2022

The Amazon Connect Contact Flows, located under backend/connect/contact_flows There are four contact flows for this demo with files names AgentWhisper , CustomerWaiting , InboundCall and OutboundCall. The Amazon API Gateway instance Appointments. Edit API Gateway route: Go to the API Gateway console. Deploy the solution.

APIs 86

APIs Self service Accountability Scripts 86