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 123

APIs Scripts Entertainment Personalization 123

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 124

Scripts APIs Enterprise Accountability 124

AWS Machine Learning

JANUARY 24, 2025

These steps might involve both the use of an LLM and external data sources and APIs. Agent plugin controller This component is responsible for the API integration to external data sources and APIs. The LLM agent is an orchestrator of a set of steps that might be necessary to complete the desired request.

APIs 114

APIs Scripts Best practices Management 114

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 124

APIs Scripts Real estate Accountability 124

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 133

Chatbots APIs Engineering Enterprise 133

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 124

Personalization APIs Scripts Technical Support 124

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 116

Scripts APIs Engineering Enterprise 116

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

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

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 131

Management APIs Engineering Government 131

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 107

APIs Scripts Enterprise Big data 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 98

Scripts APIs Construction Finance 98

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 130

Scripts Accountability APIs Engineering 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 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

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 129

APIs Engineering Scripts Construction 129

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

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 137

APIs Engineering Analytics Scripts 137

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 121

APIs Healthcare Scripts Engineering 121

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

NOVEMBER 15, 2024

The rapid advancement of generative AI promises transformative innovation, yet it also presents significant challenges. For early detection, implement custom testing scripts that run toxicity evaluations on new data and model outputs continuously. Amazon Bedrock Knowledge Bases manages the end-to-end RAG workflow for you.

APIs 110

APIs Government Best practices Metrics 110

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 132

Healthcare APIs Scripts Metrics 132

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

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 125

Analytics APIs Engineering Construction 125

AWS Machine Learning

SEPTEMBER 18, 2023

Each stage in the ML workflow is broken into discrete steps, with its own script that takes input and output parameters. In the following code, the desired number of actors is passed in as an input argument to the script. Let’s look at sections of the scripts that perform this data preprocessing. get("OfflineStoreConfig").get("S3StorageConfig").get("ResolvedOutputS3Uri")

Scripts 129

Scripts APIs Government Construction 129

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. It only defines the shape of the output tensor but not the actual values.

APIs 98

APIs Engineering Scripts Benchmark 98

AWS Machine Learning

APRIL 29, 2024

Dataset collection We followed the methodology outlined in the PMC-Llama paper [6] to assemble our dataset, which includes PubMed papers sourced from the Semantic Scholar API and various medical texts cited within the paper, culminating in a comprehensive collection of 88 billion tokens. Create and launch ParallelCluster in the VPC.

APIs 121

APIs Healthcare Scripts Enterprise 121

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. Different prompt engineering techniques include: Zero-shot – A single question is presented to the model without any additional clues. create-stack.sh

Scripts 124

Scripts Chatbots Accountability Multi-channel support 124

AWS Machine Learning

APRIL 19, 2024

Solution overview In this section, we present a generic architecture that is similar to the one we use for our own workloads, which allows elastic deployment of models using efficient auto scaling based on custom metrics. The reverse proxy collects metrics about calls to the service and exposes them via a standard metrics API to Prometheus.

Metrics 123

Metrics APIs Scripts Construction 123

AWS Machine Learning

JANUARY 11, 2023

In this post, we present a prototype AWS architecture that ingests our news feeds using RD Libraries and enhances them with machine learning (ML) model predictions using Amazon SageMaker , a fully managed ML service from AWS. We present this prototype in a series of three detailed blueprints. Building and deploying the prototype.

Scripts 95

Scripts Finance Enterprise Engineering 95

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. To use a large language model in SageMaker, you need an inferencing script specific for the model, which includes steps like model loading, parallelization and more.

Scripts 101

Scripts APIs Government Engineering 101

AWS Machine Learning

MAY 5, 2023

Using architecture diagrams as an example, the solution needs to search through reference links and technical documents for architecture diagrams and identify the services present. 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.

Engineering 103

Engineering APIs Scripts Enterprise 103

AWS Machine Learning

MAY 22, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

Scripts 134

Scripts Engineering Accountability APIs 134