AWS Machine Learning Blog

NOVEMBER 14, 2024

We recently announced the general availability of cross-account sharing of Amazon SageMaker Model Registry using AWS Resource Access Manager (AWS RAM) , making it easier to securely share and discover machine learning (ML) models across your AWS accounts.

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JUNE 26, 2023

These techniques utilize various machine learning (ML) based approaches. 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.

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AWS Machine Learning Blog

OCTOBER 20, 2023

Customers of every size and industry are innovating on AWS by infusing machine learning (ML) into their products and services. Recent developments in generative AI models have further sped up the need of ML adoption across industries.

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NOVEMBER 24, 2023

With that, the need for data scientists and machine learning (ML) engineers has grown significantly. Data scientists and ML engineers require capable tooling and sufficient compute for their work. Data scientists and ML engineers require capable tooling and sufficient compute for their work.

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AWS Machine Learning Blog

AUGUST 12, 2024

Instead, organizations are increasingly looking to take advantage of transformative technologies like machine learning (ML) and artificial intelligence (AI) to deliver innovative products, improve outcomes, and gain operational efficiencies at scale.

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NOVEMBER 19, 2024

The solution workflow consists of the following steps: The user accesses a smart search portal and lands on a web interface deployed on AWS Amplify. The API is integrated with AWS Lambda , which processes the user query and generates the answers based on available documents and user access using retrieval augmented generation (RAG).

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AWS Machine Learning Blog

OCTOBER 16, 2024

DPG Media chose Amazon Transcribe for its ease of transcription and low maintenance, with the added benefit of incremental improvements by AWS over the years. The flexibility to experiment with multiple models was appreciated, and there are plans to try out Anthropic Claude Opus when it becomes available in their desired AWS Region.

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Data Science Dojo

OCTOBER 31, 2024

Growth Outlook: Companies like Google DeepMind, NASA’s Jet Propulsion Lab, and IBM Research actively seek research data scientists for their teams, with salaries typically ranging from $120,000 to $180,000. With the continuous growth in AI, demand for remote data science jobs is set to rise.

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AWS Machine Learning Blog

OCTOBER 30, 2023

Amazon Bedrock is a fully managed service provided by AWS that offers developers access to foundation models (FMs) and the tools to customize them for specific applications. Customers are building innovative generative AI applications using Amazon Bedrock APIs using their own proprietary data.

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JUNE 3, 2025

In the following section, we dive deep into these steps and the AWS services used. They needed a solution that could support rapid expansion, handle high data volumes, and deliver consistent performance across AWS Regions. About the Authors Ray Wang is a Senior Solutions Architect at AWS.

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AWS Machine Learning Blog

MARCH 15, 2024

Many organizations are implementing machine learning (ML) to enhance their business decision-making through automation and the use of large distributed datasets. With increased access to data, ML has the potential to provide unparalleled business insights and opportunities.

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AWS Machine Learning Blog

FEBRUARY 21, 2025

Lets assume that the question What date will AWS re:invent 2024 occur? The corresponding answer is also input as AWS re:Invent 2024 takes place on December 26, 2024. If the question was Whats the schedule for AWS events in December?, This setup uses the AWS SDK for Python (Boto3) to interact with AWS services.

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AWS Machine Learning Blog

MARCH 8, 2023

Amazon SageMaker is a fully managed machine learning (ML) service. With SageMaker, data scientists and developers can quickly and easily build and train ML models, and then directly deploy them into a production-ready hosted environment. We add this data to Snowflake as a new table.

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IBM Journey to AI blog

AUGUST 12, 2024

Driven by significant advancements in computing technology, everything from mobile phones to smart appliances to mass transit systems generate and digest data, creating a big data landscape that forward-thinking enterprises can leverage to drive innovation. However, the big data landscape is just that.

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Smart Data Collective

FEBRUARY 20, 2022

AWS (Amazon Web Services), the comprehensive and evolving cloud computing platform provided by Amazon, is comprised of infrastructure as a service (IaaS), platform as a service (PaaS) and packaged software as a service (SaaS). With its wide array of tools and convenience, AWS has already become a popular choice for many SaaS companies.

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AWS Machine Learning Blog

SEPTEMBER 18, 2024

The ZMP analyzes billions of structured and unstructured data points to predict consumer intent by using sophisticated artificial intelligence (AI) to personalize experiences at scale. Hosted on Amazon ECS with tasks run on Fargate, this platform streamlines the end-to-end ML workflow, from data ingestion to model deployment.

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AWS Machine Learning Blog

DECEMBER 4, 2023

In this post, we explain how we built an end-to-end product category prediction pipeline to help commercial teams by using Amazon SageMaker and AWS Batch , reducing model training duration by 90%. An important aspect of our strategy has been the use of SageMaker and AWS Batch to refine pre-trained BERT models for seven different languages.

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AWS Machine Learning Blog

OCTOBER 29, 2024

This post is part of an ongoing series on governing the machine learning (ML) lifecycle at scale. To start from the beginning, refer to Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker.

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AWS Machine Learning Blog

JUNE 11, 2025

Gardenia Technologies, a data analytics company, partnered with the AWS Prototyping and Cloud Engineering (PACE) team to develop Report GenAI , a fully automated ESG reporting solution powered by the latest generative AI models on Amazon Bedrock. LangChain offers deep integration with AWS using the first-party langchain-aws module.

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AWS Machine Learning Blog

FEBRUARY 26, 2024

By using AWS services, our architecture provides real-time visibility into LLM behavior and enables teams to quickly identify and address any issues or anomalies. In this post, we demonstrate a few metrics for online LLM monitoring and their respective architecture for scale using AWS services such as Amazon CloudWatch and AWS Lambda.

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AWS Machine Learning Blog

NOVEMBER 29, 2023

Data preparation is a crucial step in any machine learning (ML) workflow, yet it often involves tedious and time-consuming tasks. Amazon SageMaker Canvas now supports comprehensive data preparation capabilities powered by Amazon SageMaker Data Wrangler.

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APRIL 21, 2025

In this post, to address the aforementioned challenges, we introduce an automated evaluation framework that is deployable on AWS. We then present a typical evaluation workflow, followed by our AWS-based solution that facilitates this process. The UI service can be run locally in a Docker container or deployed to AWS Fargate.

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AWS Machine Learning Blog

DECEMBER 14, 2023

This is a customer post jointly authored by ICL and AWS employees. To overcome this business challenge, ICL decided to develop in-house capabilities to use machine learning (ML) for computer vision (CV) to automatically monitor their mining machines.

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AWS Machine Learning Blog

DECEMBER 7, 2023

In this post, we describe the end-to-end workforce management system that begins with location-specific demand forecast, followed by courier workforce planning and shift assignment using Amazon Forecast and AWS Step Functions. AWS Step Functions automatically initiate and monitor these workflows by simplifying error handling.

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AWS Machine Learning Blog

NOVEMBER 12, 2024

You may check out additional reference notebooks on aws-samples for how to use Meta’s Llama models hosted on Amazon Bedrock. You can implement these steps either from the AWS Management Console or using the latest version of the AWS Command Line Interface (AWS CLI). Solutions Architect at AWS. Varun Mehta is a Sr.

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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. The example extracts and contextualizes the buildspec-1-10-2.yml

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AWS Machine Learning Blog

DECEMBER 12, 2023

In this post, we’ll summarize training procedure of GPT NeoX on AWS Trainium , a purpose-built machine learning (ML) accelerator optimized for deep learning training. M tokens/$) trained such models with AWS Trainium without losing any model quality. We’ll outline how we cost-effectively (3.2 billion in Pythia. 2048 256 10.4

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Pickl AI

FEBRUARY 23, 2025

Summary: Big Data tools empower organizations to analyze vast datasets, leading to improved decision-making and operational efficiency. Ultimately, leveraging Big Data analytics provides a competitive advantage and drives innovation across various industries.

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AWS Machine Learning Blog

SEPTEMBER 3, 2024

Harnessing the power of big data has become increasingly critical for businesses looking to gain a competitive edge. However, managing the complex infrastructure required for big data workloads has traditionally been a significant challenge, often requiring specialized expertise.

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Dataconomy

FEBRUARY 6, 2024

With the ability to analyze a vast amount of data in real-time, identify patterns, and detect anomalies, AI/ML-powered tools are enhancing the operational efficiency of businesses in the IT sector. Why does AI/ML deserve to be the future of the modern world? Let’s understand the crucial role of AI/ML in the tech industry.

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AWS Machine Learning Blog

JUNE 26, 2023

Machine learning (ML) administrators play a critical role in maintaining the security and integrity of ML workloads. To address this challenge, AWS introduced Amazon SageMaker Role Manager in December 2022. Their primary focus is to ensure that users operate with the utmost security, adhering to the principle of least privilege.

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AWS Machine Learning Blog

MARCH 3, 2023

Machine learning (ML) can help companies make better business decisions through advanced analytics. Companies across industries apply ML to use cases such as predicting customer churn, demand forecasting, credit scoring, predicting late shipments, and improving manufacturing quality. He is very passionate about data-driven AI.

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AWS Machine Learning Blog

MARCH 18, 2025

With this launch, you can now deploy NVIDIAs optimized reranking and embedding models to build, experiment, and responsibly scale your generative AI ideas on AWS. As part of NVIDIA AI Enterprise available in AWS Marketplace , NIM is a set of user-friendly microservices designed to streamline and accelerate the deployment of generative AI.

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DECEMBER 11, 2024

Second, because data, code, and other development artifacts like machine learning (ML) models are stored within different services, it can be cumbersome for users to understand how they interact with each other and make changes. SageMaker Unied Studio is an integrated development environment (IDE) for data, analytics, and AI.

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AWS Machine Learning Blog

AUGUST 15, 2024

Starting today, you can interactively prepare large datasets, create end-to-end data flows, and invoke automated machine learning (AutoML) experiments on petabytes of data—a substantial leap from the previous 5 GB limit. Organizations often struggle to extract meaningful insights and value from their ever-growing volume of data.

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AWS Machine Learning Blog

JANUARY 6, 2023

The recently published IDC MarketScape: Asia/Pacific (Excluding Japan) AI Life-Cycle Software Tools and Platforms 2022 Vendor Assessment positions AWS in the Leaders category. The tools are typically used by data scientists and ML developers from experimentation to production deployment of AI and ML solutions.

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AWS Machine Learning Blog

AUGUST 31, 2023

As Artificial Intelligence (AI) and Machine Learning (ML) technologies have become mainstream, many enterprises have been successful in building critical business applications powered by ML models at scale in production.

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