AWS Machine Learning

SEPTEMBER 20, 2024

Amazon Bedrock agents use LLMs to break down tasks, interact dynamically with users, run actions through API calls, and augment knowledge using Amazon Bedrock Knowledge Bases. In this post, we demonstrate how to use Amazon Bedrock Agents with a web search API to integrate dynamic web content in your generative AI application.

APIs 105

APIs Chatbots Construction Engineering 105

AWS Machine Learning

MARCH 15, 2023

The best practice for migration is to refactor these legacy codes using the Amazon SageMaker API or the SageMaker Python SDK. SageMaker runs the legacy script inside a processing container. Step Functions is a serverless workflow service that can control SageMaker APIs directly through the use of the Amazon States Language.

Scripts 144

Scripts APIs Engineering Construction 144

AWS Machine Learning

AUGUST 2, 2024

Earnings calls are live conferences where executives present an overview of results, discuss achievements and challenges, and provide guidance for upcoming periods. Traditionally, earnings call scripts have followed similar templates, making it a repeatable task to generate them from scratch each time.

Engineering 131

Engineering Scripts Metrics Advertising 131

AWS Machine Learning

JANUARY 8, 2024

The first allows you to run a Python script from any server or instance including a Jupyter notebook; this is the quickest way to get started. In the following sections, we first describe the script solution, followed by the AWS CDK construct solution. The following diagram illustrates the sequence of events within the script.

Scripts 123

Scripts Construction APIs Healthcare 123

AWS Machine Learning

OCTOBER 24, 2024

The retrieve_and_generate API does both the retrieval and a call to an FM (Amazon Titan or Anthropic’s Claude family of models on Amazon Bedrock ), for a fully managed solution. When the quotation-checking function fails to find a quotation in the documents, it means only that the quotation isn’t present verbatim in the text.

Chatbots 92

Chatbots Metrics Scripts APIs 92

AWS Machine Learning

NOVEMBER 30, 2023

You then perform a search against OpenSearch Service with the names and the embedding from the article to retrieve images that are semantically similar with the presence of the given celebrity, if present. The result from the multimodal model scores the images with a scarf present higher.

Scripts 124

Scripts APIs Entertainment Accountability 124

AWS Machine Learning

SEPTEMBER 8, 2023

Amazon Rekognition makes it easy to add image analysis capability to your applications without any machine learning (ML) expertise and comes with various APIs to fulfil use cases such as object detection, content moderation, face detection and analysis, and text and celebrity recognition, which we use in this example.

APIs 124

APIs Scripts Entertainment Personalization 124

AWS Machine Learning

JULY 17, 2024

In this post, we’re using the APIs for AWS Support , AWS Trusted Advisor , and AWS Health to programmatically access the support datasets and use the Amazon Q Business native Amazon Simple Storage Service (Amazon S3) connector to index support data and provide a prebuilt chatbot web experience. Synchronize the data source to index the data.

Scripts 125

Scripts APIs Enterprise Accountability 125

AWS Machine Learning

AUGUST 1, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading artificial intelligence (AI) companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API. The scripts for fine-tuning and evaluation are available on the GitHub repository.

APIs 125

APIs Scripts Real estate Accountability 125

AWS Machine Learning

MAY 16, 2024

The main AWS services used are SageMaker, Amazon EMR , AWS CodeBuild , Amazon Simple Storage Service (Amazon S3), Amazon EventBridge , AWS Lambda , and Amazon API Gateway. Real-time recommendation inference The inference phase consists of the following steps: The client application makes an inference request to the API gateway.

Personalization 125

Personalization APIs Scripts Technical Support 125

AWS Machine Learning

MARCH 27, 2025

Refer to Getting started with the API to set up your environment to make Amazon Bedrock requests through the AWS API. Test the code using the native inference API for Anthropics Claude The following code uses the native inference API to send a text message to Anthropics Claude. client = boto3.client("bedrock-runtime",

Education 110

Education Engineering APIs Enterprise 110

AWS Machine Learning

FEBRUARY 19, 2024

Chatbots also offer valuable data-driven insights into customer behavior while scaling effortlessly as the user base grows; therefore, they present a cost-effective solution for engaging customers. Clone the GitHub repo The solution presented in this post is available in the following GitHub repo. model in Amazon Bedrock.

Chatbots 134

Chatbots APIs Engineering Enterprise 134

AWS Machine Learning

JULY 25, 2024

Streamline content creation – Amazon Q can assist in generating drafts, outlines, and even complete content pieces (such as reports, articles, or presentations) by drawing on the knowledge and data stored in SharePoint. Any additional mappings need to be set in the user store using the user store APIs.

Scripts 117

Scripts APIs Engineering Enterprise 117

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 117

Scripts APIs Engineering Enterprise 117

AWS Machine Learning

JULY 24, 2023

If the model changes on the server side, the client has to know and change its API call to the new endpoint accordingly. Clone the Github repository The GitHub repo provides all the scripts necessary to deploy models using FastAPI on NeuronCores on AWS Inferentia instances. code as the entry point. compiled-model-bs-{batch_size}.pt')

Scripts 98

Scripts APIs Best practices Engineering 98

AWS Machine Learning

JANUARY 5, 2024

Continuous integration and continuous delivery (CI/CD) pipeline – Using the customer’s GitHub repository enabled code versioning and automated scripts to launch pipeline deployment whenever new versions of the code are committed. Wipro has used the input filter and join functionality of SageMaker batch transformation API.

Management 132

Management APIs Engineering Government 132

AWS Machine Learning

JUNE 15, 2022

Instead of presenting each facet individually as a list, hierarchical facets enable defining a parent-child relationship between facets to shape the scope of the search results. If you just want to read about this feature without running it yourself, you can refer to the Python script facet-search-query.py Solution overview.

APIs 97

APIs Scripts Technology Engineering 97

AWS Machine Learning

NOVEMBER 17, 2022

JumpStart APIs allow you to programmatically deploy and fine-tune a vast selection of JumpStart-supported pre-trained models on your own datasets. In this post, we present a methodology to easily run multiple models and compare their outputs on three dimensions of interest: model accuracy, training time, and inference time.

APIs 98

APIs Scripts Metrics 98

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 108

APIs Scripts Enterprise Big data 108

AWS Machine Learning

JULY 11, 2024

Retrieval Augmented Generation (RAG) is a popular paradigm that provides additional knowledge to large language models (LLMs) from an external source of data that wasn’t present in their training corpus. Python script that serves as the entry point. expand(token_embeddings.size()).float() tolist()} After creating the inference.py

Scripts 131

Scripts Accountability APIs Engineering 131

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 98

Scripts APIs Construction Finance 98

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 108

APIs Scripts Enterprise Big data 108

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 98

APIs Scripts Enterprise Big data 98

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 98

Scripts APIs Real estate Entertainment 98

AWS Machine Learning

NOVEMBER 14, 2023

The solution also uses Amazon Bedrock , a fully managed service that makes foundation models (FMs) from Amazon and third-party model providers accessible through the AWS Management Console and APIs. For this post, we use the Amazon Bedrock API via the AWS SDK for Python. The script instantiates the Amazon Bedrock client using Boto3.

APIs 130

APIs Engineering Scripts Education 130

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 98

Scripts APIs Engineering Consulting 98

AWS Machine Learning

MAY 23, 2024

Despite their computational benefits, training and fine-tuning large MoE models efficiently presents some challenges. The SMP library uses NVIDIA Megatron to implement expert parallelism and support training MoE models, and runs on top of PyTorch Fully Sharded Data Parallel (FSDP) APIs. In this example, we use SageMaker training jobs.

APIs 130

APIs Engineering Scripts Construction 130

AWS Machine Learning

AUGUST 29, 2023

The presented MLOps workflow provides a reusable template for managing the ML lifecycle through automation, monitoring, auditability, and scalability, thereby reducing the complexities and costs of maintaining batch inference workloads in production.

Scripts 98

Scripts APIs Enterprise Accountability 98

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 101

Scripts APIs Entertainment Construction 101

AWS Machine Learning

DECEMBER 29, 2022

Users can also interact with data with ODBC, JDBC, or the Amazon Redshift Data API. However, working with data in the cloud can present challenges, such as the need to remove organizational data silos, maintain security and compliance, and reduce complexity by standardizing tooling. Solution overview.

APIs 138

APIs Engineering Analytics Scripts 138

AWS Machine Learning

JUNE 23, 2023

For data scientists, moving machine learning (ML) models from proof of concept to production often presents a significant challenge. FastAPI is a modern, high-performance web framework for building APIs with Python. It can be cumbersome to manage the process, but with the right tool, you can significantly reduce the required effort.

APIs 101

APIs Scripts Engineering Accountability 101

AWS Machine Learning

SEPTEMBER 14, 2023

Amazon API Gateway hosts a REST API with various endpoints to handle user requests that are authenticated using Amazon Cognito. The service analyzes the text and identifies any PII entities present within the query. The web application front-end is hosted on AWS Amplify. Confluence, Microsoft SharePoint, Google Drive, Jira, etc.)

APIs 122

APIs Healthcare Scripts Engineering 122

AWS Machine Learning

APRIL 5, 2024

Gramener’s GeoBox solution empowers users to effortlessly tap into and analyze public geospatial data through its powerful API, enabling seamless integration into existing workflows. With the SearchRasterDataCollection API, SageMaker provides a purpose-built functionality to facilitate the retrieval of satellite imagery.

APIs 132

APIs Engineering Analytics Healthcare 132

AWS Machine Learning

AUGUST 30, 2023

In order to run inference through SageMaker API, make sure to pass the Predictor class. 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 133

Healthcare APIs Scripts Metrics 133

AWS Machine Learning

JANUARY 6, 2023

In this post, we present a solution to handle OOC situations through knowledge graph-based embedding search using the k-nearest neighbor (kNN) search capabilities of OpenSearch Service. Creates an API Gateway that adds an additional layer of security between the web app user interface and Lambda. Solution overview. from your terminal.

Entertainment 101

Entertainment APIs Scripts Analytics 101

AWS Machine Learning

JULY 26, 2023

This notebook presents an end-to-end example of how to compile a Stable Diffusion model, save the compiled Neuron models, and load it into the runtime for inference. 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.

Scripts 98

Scripts APIs Benchmark Engineering 98

AWS Machine Learning

JULY 5, 2022

Lifecycle configurations (LCCs) are shell scripts to automate customization for your Studio environments, such as installing JupyterLab extensions, preloading datasets, and setting up source code repositories. LCC scripts are triggered by Studio lifecycle events, such as starting a new Studio notebook. Apply the script (see below).

Scripts 98

Scripts Engineering APIs Consulting 98