AWS Machine Learning Blog

OCTOBER 5, 2023

In this post, we walk through how to fine-tune Llama 2 on AWS Trainium , a purpose-built accelerator for LLM training, to reduce training times and costs. We review the fine-tuning scripts provided by the AWS Neuron SDK (using NeMo Megatron-LM), the various configurations we used, and the throughput results we saw.

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IBM Data Science in Practice

MARCH 8, 2023

You can then export the model and deploy it on Amazon Sagemaker on Amazon Web Server (AWS). If you are set up with the required systems, you can download the sample project and complete the steps for hands-on learning. The example model predicts how likely a customer is to enroll in a Demand Response Program of a Utilities Company.

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AWS Machine Learning Blog

MARCH 21, 2025

AWS Lambda AWS Lambda is a compute service that runs code in response to triggers such as changes in data, changes in application state, or user actions. Prerequisites If youre new to AWS, you first need to create and set up an AWS account. We download the documents and store them under a samples folder locally.

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AWS Machine Learning Blog

MARCH 15, 2024

To mitigate these risks, the FL model uses personalized training algorithms and effective masking and parameterization before sharing information with the training coordinator. Therefore, ML creates challenges for AWS customers who need to ensure privacy and security across distributed entities without compromising patient outcomes.

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AWS Machine Learning Blog

JANUARY 17, 2024

Today, we’re excited to announce the availability of Llama 2 inference and fine-tuning support on AWS Trainium and AWS Inferentia instances in Amazon SageMaker JumpStart. In this post, we demonstrate how to deploy and fine-tune Llama 2 on Trainium and AWS Inferentia instances in SageMaker JumpStart.

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Flipboard

JUNE 26, 2023

In this post, we look at how we can use AWS Glue and the AWS Lake Formation ML transform FindMatches to harmonize (deduplicate) customer data coming from different sources to get a complete customer profile to be able to provide better customer experience. Run the AWS Glue ML transform job.

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AWS Machine Learning Blog

JANUARY 21, 2025

In this post, we show you how Amazon Web Services (AWS) helps in solving forecasting challenges by customizing machine learning (ML) models for forecasting. To learn more about these algorithms visit Algorithms support for time-series forecasting in the Amazon SageMaker documentation. To download a copy of this dataset, visit.

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AWS Machine Learning Blog

APRIL 7, 2025

Virginia) AWS Region. Prerequisites To try the Llama 4 models in SageMaker JumpStart, you need the following prerequisites: An AWS account that will contain all your AWS resources. An AWS Identity and Access Management (IAM) role to access SageMaker AI. b64encode(img).decode('utf-8') b64encode(response.content).decode('utf-8')

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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

NOVEMBER 15, 2023

Understanding up front which preprocessing techniques and algorithm types provide best results reduces the time to develop, train, and deploy the right model. An AutoML tool applies a combination of different algorithms and various preprocessing techniques to your data. The following diagram presents the overall solution workflow.

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AWS Machine Learning Blog

MARCH 8, 2023

It also provides common ML algorithms that are optimized to run efficiently against extremely large data in a distributed environment. This post shows a way to do this using Snowflake as the data source and by downloading the data directly from Snowflake into a SageMaker Training job instance. AWS Region Link us-east-1 (N.

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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. The following screenshot shows our example dashboard.

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AWS Machine Learning Blog

MAY 1, 2024

Prerequisites First-time users need an AWS account and AWS Identity and Access Management (IAM) role with SageMaker, Amazon Bedrock, and Amazon Simple Storage Service (Amazon S3) access. Prepare your dataset Complete the following steps to prepare your dataset: Download the following CSV dataset of question-answer pairs.

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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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AWS Machine Learning Blog

MAY 30, 2023

In 2021, we launched AWS Support Proactive Services as part of the AWS Enterprise Support plan. With SageMaker training jobs, you can bring your own algorithm or choose from more than 25 built-in algorithms. From a pricing perspective, you are charged for Downloading, Training, and Uploading phases.

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AWS Machine Learning Blog

SEPTEMBER 23, 2024

Prerequisties The proposed solution can be implemented in a personal AWS environment using the code that we provide. Before running the labs in this post, ensure you have the following: An AWS account. The appropriate AWS Identity and Access Management (IAM) permissions to access services used in the lab.

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DrivenData Labs

NOVEMBER 14, 2023

VIIRS is similar to MODIS, and its snow cover and sea ice algorithms are designed to be the newer continuation of MODIS data. VIIRS has higher spatial resolution for certain spectral bands, while MODIS has higher resolution for others. For example, VIIRS has higher resolution for the thermal bands that are useful for detecting forest fires.

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AWS Machine Learning Blog

FEBRUARY 21, 2025

There are various techniques of preference alignment, including proximal policy optimization (PPO), direct preference optimization (DPO), odds ratio policy optimization (ORPO), group relative policy optimization (GRPO), and other algorithms, that can be used in this process. Set up a SageMaker notebook instance.

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AWS Machine Learning Blog

OCTOBER 9, 2024

The service, which was launched in March 2021, predates several popular AWS offerings that have anomaly detection, such as Amazon OpenSearch , Amazon CloudWatch , AWS Glue Data Quality , Amazon Redshift ML , and Amazon QuickSight. To use this feature, you can write rules or analyzers and then turn on anomaly detection in AWS Glue ETL.

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AWS Machine Learning Blog

MAY 16, 2024

Therefore, we decided to introduce a deep learning-based recommendation algorithm that can identify not only linear relationships in the data, but also more complex relationships. Recommendation model using NCF NCF is an algorithm based on a paper presented at the International World Wide Web Conference in 2017.

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AWS Machine Learning Blog

MARCH 25, 2024

Amazon Transcribe is an AWS service that allows customers to convert speech to text in either batch or streaming mode. AWS is responsible for protecting the global infrastructure that runs all of the AWS Cloud. This content includes the security configuration and management tasks for the AWS services that you use.

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AWS Machine Learning Blog

JULY 18, 2023

The built-in BlazingText algorithm offers optimized implementations of Word2vec and text classification algorithms. We walk you through the following steps to set up our spam detector model: Download the sample dataset from the GitHub repo. With the BlazingText algorithm, you can scale to large datasets.

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AWS Machine Learning Blog

SEPTEMBER 7, 2023

The algorithm trained in this blog post is called “ Conservative Q Learning ” (CQL). Measurement data is produced at the edge by a piece of industrial equipment (here simulated by an AWS Lambda function). AWS Glue catalogs the data and makes it queryable using Amazon Athena. Train the algorithm on that data.

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AWS Machine Learning Blog

MAY 8, 2024

Amazon SageMaker JumpStart provides a suite of built-in algorithms , pre-trained models , and pre-built solution templates to help data scientists and machine learning (ML) practitioners get started on training and deploying ML models quickly. You can use these algorithms and models for both supervised and unsupervised learning.

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Flipboard

FEBRUARY 7, 2023

The following example illustrates Studio Lab running a Jupyter notebook that downloads TCIA prostate MRI data, segments it using MONAI, and displays the results using itkWidgets. The first SageMaker notebook shows how to download DICOM images from TCIA and visualize those images using the cinematic volume rendering capabilities of itkWidgets.

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AWS Machine Learning Blog

MAY 4, 2023

Amazon Forecast is an ML-based time series forecasting service that includes algorithms that are based on over 20 years of forecasting experience used by Amazon.com , bringing the same technology used at Amazon to developers as a fully managed service, removing the need to manage resources. A deployed template is referred to as a stack.

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AWS Machine Learning Blog

SEPTEMBER 25, 2024

SageMaker JumpStart is a machine learning (ML) hub that provides access to algorithms, models, and ML solutions so you can quickly get started with ML. models are available in SageMaker JumpStart initially in the US East (Ohio) AWS Region. An AWS Identity and Access Management (IAM) role to access SageMaker.

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AWS Machine Learning Blog

SEPTEMBER 18, 2024

Integrating it with the range of AWS serverless computing, networking, and content delivery services like AWS Lambda , Amazon API Gateway , and AWS Amplify facilitates the creation of an interactive tool to generate dynamic, responsive, and adaptive logos. We recommend using the us-east-1 Obtain access to the Stability SDXL 1.0

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AWS Machine Learning Blog

MAY 22, 2024

Furthermore, having factoid product descriptions can increase customer satisfaction by enabling a more personalized buying experience and improving the algorithms for recommending more relevant products to users, which raise the probability that users will make a purchase. For details, see Creating an AWS account.

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AWS Machine Learning Blog

JULY 29, 2024

Amazon Forecast is a fully managed service that uses statistical and machine learning (ML) algorithms to deliver highly accurate time series forecasts. With SageMaker Canvas, you get faster model building , cost-effective predictions, advanced features such as a model leaderboard and algorithm selection, and enhanced transparency.

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AWS Machine Learning Blog

SEPTEMBER 12, 2024

Prerequisites To implement this solution, you need the following: An AWS account with privileges to create AWS Identity and Access Management (IAM) roles and policies. Basic familiarity with SageMaker and AWS services that support LLMs. For more information, see Overview of access management: Permissions and policies.

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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

APRIL 19, 2024

We used AWS services including Amazon Bedrock , Amazon SageMaker , and Amazon OpenSearch Serverless in this solution. In this series, we use the slide deck Train and deploy Stable Diffusion using AWS Trainium & AWS Inferentia from the AWS Summit in Toronto, June 2023 to demonstrate the solution.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

Prerequisites To try out this solution using SageMaker JumpStart, you need the following prerequisites: An AWS account that will contain all of your AWS resources. An AWS Identity and Access Management (IAM) role to access SageMaker. He focuses on developing scalable machine learning algorithms.

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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. Step 1: Download the map files for the region you want to cover. The map extracts can be downloaded from Geofrabrik. Up until recently, I thought there were only two ways to do this: 1. However, for sake of completeness, I will add the instructions here.

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AWS Machine Learning Blog

OCTOBER 17, 2024

Amazon Transcribe uses advanced speech recognition algorithms and machine learning (ML) models to accurately partition speakers and transcribe the audio, handling various accents, background noise, and other challenges. Deployment, as described below, is currently supported only in the US West (Oregon) us-west-2 AWS Region.

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AWS Machine Learning Blog

OCTOBER 6, 2023

Moreover, auto-generated tags or attributes can substantially improve product recommendation algorithms. If you want to download the model from Hugging Face directly, you can set the option.model_id parameter in the serving.properties file as the model id of a pre-trained model hosted inside a model repository on huggingface.co.

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