AWS Machine Learning

FEBRUARY 13, 2023

In this post, we enable the provisioning of different components required for performing log analysis using Amazon SageMaker on AWS DeepRacer via AWS CDK constructs. With the help of the AWS CDK, we can version control our provisioned resources and have a highly transportable environment that complies with enterprise-level best practices.

Scripts 75

Scripts Best practices Transportation Construction 75

AWS Machine Learning

SEPTEMBER 1, 2023

Each business unit has each own set of development (automated model training and building), preproduction (automatic testing), and production (model deployment and serving) accounts to productionize ML use cases, which retrieve data from a centralized or decentralized data lake or data mesh, respectively.

Engineering 106

Engineering Accountability Construction APIs 106

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 98

Scripts APIs Government Analytics 98

AWS Machine Learning

FEBRUARY 29, 2024

You can also add data incrementally by importing records using the Amazon Personalize console or API. Prerequisites You should have the following prerequisites: An AWS account. After your historical data is imported, you can continue to provide new data in real time by sending user interaction events.

Personalization 93

Personalization Accountability Entertainment Construction 93

AWS Machine Learning

JULY 24, 2023

A recent initiative is to simplify the difficulty of constructing search expressions by autofilling patent search queries using state-of-the-art text generation models. Because there is no such existing feature in a patent search engine (to their best knowledge), Patsnap believes adding this feature will increase end-user stickiness.

APIs 68

APIs Engineering Construction Benchmark 68

AWS Machine Learning

AUGUST 1, 2023

Furthermore, proprietary models typically come with user-friendly APIs and SDKs, streamlining the integration process with your existing systems and applications. It offers an easy-to-use API and Python SDK, balancing quality and affordability. As a best practice, let’s save our work for future use.

Healthcare 75

Healthcare APIs Scripts Engineering 75

AWS Machine Learning

JANUARY 8, 2024

The second approach is a turnkey deployment of various infrastructure components using AWS Cloud Development Kit (AWS CDK) constructs. The AWS CDK construct provides a resilient and flexible framework to process your documents and build an end-to-end IDP pipeline. Now on to our second solution for documents at scale.

Scripts 90

Scripts Construction APIs Healthcare 90

AWS Machine Learning

NOVEMBER 22, 2023

By using the Framework, you will learn operational and architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable workloads in the cloud. The AWS Well-Architected Framework helps you understand the benefits and risks of decisions you make while building workloads on AWS.

Best practices 83

Best practices APIs Accountability Enterprise 83

AWS Machine Learning

MAY 1, 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 to build generative AI applications with security, privacy, and responsible AI.

Chatbots 87

Chatbots APIs Engineering Automotive 87

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. Step Functions is a serverless workflow service that can control SageMaker APIs directly through the use of the Amazon States Language.

Scripts 124

Scripts APIs Engineering Construction 124

AWS Machine Learning

MAY 1, 2024

For interacting with AWS services, the AWS Amplify JS library for React simplifies the authentication, security, and API requests. The backend uses several serverless and event-driven AWS services, including AWS Step Functions for low-code workflows, AWS AppSync for a GraphQL API, and Amazon Translate. 1 – Translating a document.

APIs 85

APIs Construction Best practices Technology 85

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).

APIs 72

APIs Government Accountability Scripts 72

AWS Machine Learning

AUGUST 10, 2023

As recommended by AWS as a best practice , customers have used separate accounts to simplify policy management for users and isolate resources by workloads and account. To view the details of these jobs in different accounts, you need to log in to each account, find the corresponding jobs, and look into the status.

Scripts 79

Scripts Accountability Metrics APIs 79

AWS Machine Learning

SEPTEMBER 18, 2023

The combination of Ray and SageMaker provides end-to-end capabilities for scalable ML workflows, and has the following highlighted features: Distributed actors and parallelism constructs in Ray simplify developing distributed applications. Ray AI Runtime (AIR) reduces friction of going from development to production.

Scripts 103

Scripts APIs Government Construction 103

AWS Machine Learning

MARCH 28, 2024

Solution overview In this post, we demonstrate the use of Mixtral-8x7B Instruct text generation combined with the BGE Large En embedding model to efficiently construct a RAG QnA system on an Amazon SageMaker notebook using the parent document retriever tool and contextual compression technique. We use an ml.t3.medium

Telecommunications 115

Telecommunications Healthcare Transportation Accountability 115

AWS Machine Learning

DECEMBER 6, 2023

Amazon Bedrock is fully serverless with no underlying infrastructure to manage extending access to available models through a single API. In Q4’s solution, we use Amazon Bedrock as a serverless, API-based, multi-foundation model building block. LangChain supports Amazon Bedrock as a multi-foundation model API.

Chatbots 100

Chatbots APIs Engineering CRM 100

AWS Machine Learning

MAY 4, 2023

The Neuron runtime consists of kernel driver and C/C++ libraries, which provide APIs to access AWS Inferentia and Trainium Neuron devices. This file acts as an intermediary between the DJLServing APIs and the transformers-neuronx APIs. Bring your own script – In this approach, you have the option to create your own model.py

APIs 78

APIs Scripts Engineering Chatbots 78

AWS Machine Learning

MARCH 19, 2024

To enhance code generation accuracy, we propose dynamically constructing multi-shot prompts for NLQs. The dynamically constructed multi-shot prompt provides the most relevant context to the FM, and boosts the FM’s capability in advanced math calculation, time series data processing, and data acronym understanding.

Construction 118

Construction Scripts APIs Enterprise 118

AWS Machine Learning

MAY 2, 2023

The FIL backend utilizes many of these techniques by using cuML constructs and is built on C++ and the CUDA core library to optimize inference performance on GPU accelerators. The FIL backend uses cuML’s libraries to use CPU or GPU cores to accelerate learning. base}/sagemaker-tritonserver:23.02-py3".format( astype(str).tolist()

Scripts 65

Scripts Engineering Enterprise Construction 65

AWS Machine Learning

JULY 13, 2023

Amazon SageMaker distributed training jobs enable you with one click (or one API call) to set up a distributed compute cluster, train a model, save the result to Amazon Simple Storage Service (Amazon S3), and shut down the cluster when complete. colsample_bytree – Subsample ratio of columns when constructing each tree.

Metrics 69

Metrics Construction Best practices APIs 69

AWS Machine Learning

NOVEMBER 9, 2022

In this post, we discuss SageMaker multi-variant endpoints and best practices for optimization. Your application simply needs to include an API call with the target model to this endpoint to achieve low-latency, high-throughput inference. To deploy, use the endpoint_from_production_variant construct to create the endpoint.

Best practices 52

Best practices Construction Metrics Enterprise 52