AWS Machine Learning Blog

APRIL 7, 2023

To reduce the barrier to entry of ML at the edge, we wanted to demonstrate an example of deploying a pre-trained model from Amazon SageMaker to AWS Wavelength , all in less than 100 lines of code. In this post, we demonstrate how to deploy a SageMaker model to AWS Wavelength to reduce model inference latency for 5G network-based applications.

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AWS Machine Learning Blog

AUGUST 30, 2023

This post demonstrates a strategy for fine-tuning publicly available LLMs for the task of radiology report summarization using AWS services. Our solution uses the FLAN-T5 XL FM, using Amazon SageMaker JumpStart , which is an ML hub offering algorithms, models, and ML solutions.

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IBM Journey to AI blog

OCTOBER 30, 2023

In this quest, IBM and AWS have forged a strategic alliance, aiming to transition AI’s business potential from mere talk to tangible action. The AWS-IBM partnership is a symphony of strengths The collaboration between IBM and AWS is more than just a tactical alliance; it’s a symphony of strengths.

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AWS Machine Learning Blog

OCTOBER 23, 2024

The following demo shows Agent Creator in action. SnapLogic uses Amazon Bedrock to build its platform, capitalizing on the proximity to data already stored in Amazon Web Services (AWS). To address customers’ requirements about data privacy and sovereignty, SnapLogic deploys the data plane within the customer’s VPC on AWS.

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AWS Machine Learning Blog

AUGUST 26, 2024

AWS makes it possible for organizations of all sizes and developers of all skill levels to build and scale generative AI applications with security, privacy, and responsible AI. In this post, we dive into the architecture and implementation details of GenASL, which uses AWS generative AI capabilities to create human-like ASL avatar videos.

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Flipboard

NOVEMBER 30, 2023

Although it provides various entry points like the SageMaker Python SDK, AWS SDKs, the SageMaker console, and Amazon SageMaker Studio notebooks to simplify the process of training and deploying ML models at scale, customers are still looking for better ways to deploy their models for playground testing and to optimize production deployments.

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AWS Machine Learning Blog

JULY 15, 2024

Faced with manual dubbing challenges and prohibitive costs, MagellanTV sought out AWS Premier Tier Partner Mission Cloud for an innovative solution. In the backend, AWS Step Functions orchestrates the preceding steps as a pipeline. Each step is run on AWS Lambda or AWS Batch. She received her Ph.D.

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AWS Machine Learning Blog

APRIL 12, 2023

JWTs are signed using a cryptographic algorithm to ensure that the claims can’t be altered after the token is issued. Header – It contains parts like type of the token, which is JWT, the signing algorithm being used, such as HMAC SHA256 or RSA, and an optional key identifier. JWTs consist of three parts separated by dots (.):

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

In this post, we demonstrate how to build a robust real-time anomaly detection solution for streaming time series data using Amazon Managed Service for Apache Flink and other AWS managed services. It offers an AWS CloudFormation template for straightforward deployment in an AWS account. anomalyScore":0.0,"detectionPeriodStartTime":"2024-08-29

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Dataconomy

JUNE 16, 2023

For a free initial consultation call, you can email sales@gammanet.com or click “Request a Demo” on the Gamma website ([link] Go to the Gamma.AI Click “Request a Demo.” Click “ See it in action ” and wait for the demo. ” Read the text and put your information in empty boxes.

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AWS Machine Learning Blog

JUNE 29, 2023

Automatically deriving context is achieved through Amazon CloudFront headers that are included in requests such as a REST API in Amazon API Gateway that calls an AWS Lambda function to retrieve recommendations. We provide a AWS CloudFormation template to create the necessary resources.

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AWS Machine Learning Blog

DECEMBER 14, 2023

In November 2022, we announced that AWS customers can generate images from text with Stable Diffusion models in Amazon SageMaker JumpStart , a machine learning (ML) hub offering models, algorithms, and solutions. AWS provides a plethora of options and services to facilitate this endeavor.

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AWS Machine Learning Blog

NOVEMBER 17, 2023

You can deploy this solution to your AWS account using the AWS Cloud Development Kit (AWS CDK) package available in our GitHub repo. This process involves the utilization of both ML and non-ML algorithms. Using the AWS Management Console , you can create a recording configuration and link it to an Amazon IVS channel.

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AWS Machine Learning Blog

DECEMBER 14, 2023

To reduce the effort of preparing training data, we built a pre-labeling tool using AWS Step Functions that automatically pre-annotates documents by using existing tabular entity data. For the demo, we use simulated bank statements like the following example. The first technique is fuzzy matching.

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AWS Machine Learning Blog

JANUARY 31, 2024

This technique is achieved through the use of ML algorithms that enable the understanding of the meaning and context of data (semantic relationships) and the learning of complex relationships and patterns within the data (syntactic relationships). You can use it via either the Amazon Bedrock REST API or the AWS SDK.

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Flipboard

FEBRUARY 7, 2023

Although you can easily carry out smaller experiments and demos with the sample notebooks presented in this post on Studio Lab for free, it is recommended to use Amazon SageMaker Studio when you train your own medical image models at scale. Gang Fu is a Healthcare Solution Architect at AWS.

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Data Science 101

DECEMBER 20, 2019

This video demos the awesome new visualization tool from Microsoft. Best quote from the article: “It is an artform to map a business problem to an algorithm.” ” Daphne Koller talks AWS and Machine Learning for Drug Development The title says it all. What is SandDance?

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Flipboard

NOVEMBER 24, 2023

In this post, we show you how SnapLogic , an AWS customer, used Amazon Bedrock to power their SnapGPT product through automated creation of these complex DSL artifacts from human language. SnapLogic background SnapLogic is an AWS customer on a mission to bring enterprise automation to the world.

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AWS Machine Learning Blog

FEBRUARY 29, 2024

Knowledge Bases for Amazon Bedrock allows you to build performant and customized Retrieval Augmented Generation (RAG) applications on top of AWS and third-party vector stores using both AWS and third-party models. You can also use the StartIngestionJob API to trigger the sync via the AWS SDK.

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AWS Machine Learning Blog

NOVEMBER 10, 2023

We previously explored a single job optimization, visualized the outcomes for SageMaker built-in algorithm, and learned about the impact of particular hyperparameter values. In this post, we run multiple HPO jobs with a custom training algorithm and different HPO strategies such as Bayesian optimization and random search.

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AWS Machine Learning Blog

OCTOBER 17, 2023

AWS Partners like Cognizant are excited by the personalization possibilities that the Amazon Personalize Search Ranking plugin will unlock for their media and retail customers. Example use cases To explore the impact of this new feature in greater detail, let’s review an example using a dataset from the Retail Demo Store.

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AWS Machine Learning Blog

AUGUST 3, 2023

We demonstrate how you can combine well-known ML solutions with postprocessing to address this problem on the AWS Cloud. Training ML algorithms for pose estimation requires a lot of expertise and custom training data. For each option, we host an AWS Lambda function behind an API Gateway that is exposed to our mock application.

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AWS Machine Learning Blog

FEBRUARY 16, 2023

Amazon Kendra is a highly accurate and intelligent search service that enables users to search for answers to their questions from your unstructured and structured data using natural language processing and advanced search algorithms. You can skip this step if you have a pre-existing index to use for this demo.

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AWS Machine Learning Blog

AUGUST 9, 2023

To scale the proposed solution for production and streamline the deployment of AI models in the AWS environment, we demonstrate it using SageMaker endpoints. Prerequisites We have developed an AWS CloudFormation template that will create the SageMaker notebooks used to deploy the endpoints and run inference.

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AWS Machine Learning Blog

FEBRUARY 19, 2024

Multiple device and accelerator support – DJL Serving supports deploying models on CPU, GPU, and AWS Inferentia. example in this demo can be seen in the GitHub repo. This newly launched feature is available in all AWS Regions where SageMaker is available. To learn more, refer to Supported algorithms, frameworks, and instances.

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AWS Machine Learning Blog

JUNE 3, 2024

based single sign-on (SSO) methods, such as AWS IAM Identity Center. To learn more, see Secure access to Amazon SageMaker Studio with AWS SSO and a SAML application. For more information, see AWS managed policy: AmazonSageMakerCanvasAIServicesAccess. For more information, see Training modes and algorithm support.

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Dataconomy

MARCH 19, 2024

From insightful webinars and comprehensive training sessions to cutting-edge demos and more, we’ll cover all the highlights and innovations showcased at this year’s event. Integration of the new NVIDIA Blackwell GPU platform into AWS infrastructure is announced, enhancing generative AI capabilities.

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AWS Machine Learning Blog

SEPTEMBER 6, 2023

The cost savings achieved through resource sharing and simplified model management makes SageMaker MMEs an excellent choice for you to host models at scale on AWS. To learn more about Stable Diffusion models on AWS, refer to Create high-quality images with Stable Diffusion models and deploy them cost-efficiently with Amazon SageMaker.

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AWS Machine Learning Blog

AUGUST 22, 2023

Many ML algorithms train over large datasets, generalizing patterns it finds in the data and inferring results from those patterns as new unseen records are processed. Flower has an extensive implementation of FL averaging algorithms and a robust communication stack. Flower is open-sourced under Apache 2.0

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AWS Machine Learning Blog

MARCH 20, 2023

Use the AWS Command Line Interface (AWS CLI) to create an inference endpoint in SageMaker. The following example is a question answering algorithm using a BERT-base model. pt")) Clean up Refer to the Github repo for steps to clean up the AWS resources created. times greater with INT8 quantization. 2xLarge-FP32 70 110.8

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AWS Machine Learning Blog

JANUARY 17, 2023

To try out the solution in your own account, make sure that you have the following in place: An AWS account. To run this JumpStart solution and have the infrastructure deploy to your AWS account, you must create an active Amazon SageMaker Studio instance (see Onboard to Amazon SageMaker Studio ). Demo notebook.

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AWS Machine Learning Blog

MAY 2, 2023

Managed Spot Training is supported in all AWS Regions where Amazon SageMaker is currently available. If the in-memory FAISS doesn’t fit into your large dataset, we provide you with a SageMaker KNN algorithm to perform the semantic search, which also uses FAISS as the underlying searching algorithm.

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Applied Data Science

FEBRUARY 7, 2022

Pay for a Cloud provider’s API, such as Google’s, AWS, or on Azure. You can view a demo of the tool here. Whether it is planning routes for delivery services, or measuring a customer’s willingness to travel to certain locations, getting an accurate measure of distance is always key. file on their repository.

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AWS Machine Learning Blog

NOVEMBER 1, 2023

The demo implementation code is available in the following GitHub repo. Utilizing the latest Hugging Face LLM modules on Amazon SageMaker, AWS customers can now tap into the power of SageMaker deep learning containers (DLCs). About the authors Alfred Shen is a Senior AI/ML Specialist at AWS.

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AWS Machine Learning Blog

SEPTEMBER 25, 2024

The whole process is shown in the following image: Implementation steps This solution has been tested in AWS Region us-east-1. Testing the Streamlit app in a SageMaker environment is intended for a temporary demo. To set up a JupyterLab space Sign in to your AWS account and open the AWS Management Console.

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AWS Machine Learning Blog

MAY 16, 2023

JumpStart is the machine learning (ML) hub of Amazon SageMaker that provides access to foundation models in addition to built-in algorithms and end-to-end solution templates to help you quickly get started with ML. A short demo to showcase the JumpStartOpenChatKitShell is shown in the following video.

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AWS Machine Learning Blog

DECEMBER 6, 2023

When answering a new question in real time, the input question is converted to an embedding, which is used to search for and extract the most similar chunks of documents using a similarity metric, such as cosine similarity, and an approximate nearest neighbors algorithm. Choose the link with the following format to open the demo: [link].

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