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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Flipboard

JULY 7, 2025

The key here is to focus on concepts like supervised vs. unsupervised learning, regression, classification, clustering, and model evaluation. Deploying & Managing LLM applications In Production Environments: How to deploy LLMs (Large Language Models) as APIs using Hugging Face + AWS - Covers deploying LLMs as APIs in the cloud.

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AWS Machine Learning Blog

APRIL 4, 2025

They fine-tuned this model using their proprietary dataset and in-house data science expertise. Integration with existing systems on AWS: Lumi seamlessly integrated SageMaker Asynchronous Inference endpoints with their existing loan processing pipeline. The pipeline leverages several AWS services familiar to Lumis team.

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AWS Machine Learning Blog

JULY 11, 2025

Managing access control in enterprise machine learning (ML) environments presents significant challenges, particularly when multiple teams share Amazon SageMaker AI resources within a single Amazon Web Services (AWS) account. Refer to the Operating model whitepaper for best practices on account structure.

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databricks

JULY 22, 2025

Instead of running on a fixed schedule, maintenance now adapts to workload patterns and data layout to optimize cost and performance automatically. This reduces unnecessary rewrites, improving performance and lowering compute costs by avoiding full file rewrites during updates and deletes.

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AWS Machine Learning Blog

FEBRUARY 7, 2025

In this post, we dive deep into how CONXAI hosts the state-of-the-art OneFormer segmentation model on AWS using Amazon Simple Storage Service (Amazon S3), Amazon Elastic Kubernetes Service (Amazon EKS), KServe, and NVIDIA Triton. Our journey to AWS Initially, CONXAI started with a small cloud provider specializing in offering affordable GPUs.

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AWS Machine Learning Blog

FEBRUARY 25, 2025

The integration with Amazon Bedrock is achieved through the Boto3 Python module, which serves as an interface to the AWS, enabling seamless interaction with Amazon Bedrock and the deployment of the classification model. This doesnt imply that clusters coudnt be highly separable in higher dimensions.

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databricks

JULY 15, 2025

On a lightweight four-node cluster, the TTR and TTS analyses completed in 5 and 40 minutes respectively on the network described above (1,700 nodes)—all for under $10 in cloud spend. This highlights the solution’s impressive speed and cost-effectiveness.

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Data Engineering Data Engineering Data Engineer Data Engineering 144

AWS Machine Learning Blog

JUNE 27, 2025

Managing and optimizing AWS infrastructure costs is a critical challenge for organizations of all sizes. In this post, we explore how to use Amazon Q CLI with the AWS Cost Analysis MCP server to perform sophisticated cost analysis that follows AWS best practices.

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Hacker News

JULY 1, 2025

reply abrefeld 1 hour ago | prev | next [–] Data science / finance / full-stack | Python (6+ years) | Full-time | In-Person / Hybrid Location: Denver, Colorado (greater metro area) Remote: Yes, for the right team. Résumé/CV: https://www.dropbox.com/scl/fi/5j9r1z2uaaq7hz50v1kfl/Resume.

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AWS Machine Learning Blog

MARCH 25, 2025

Scenario 1: Multiple single GPU cluster In this scenario, assume youre running an endpoint with three ml.g5.2xlarge instances, each with a single GPU. The existing instances can still serve traffic, but to move the endpoint out of the failed status, you need to contact your AWS support team.

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AWS Machine Learning Blog

APRIL 1, 2025

The following code imports the necessary libraries, including Boto3 for AWS services, LangChain components, and Streamlit. Clean up When you have finished experimenting with this solution, clean up your resources to prevent AWS charges from being incurred: Empty the S3 buckets. Clone the GitHub repo to make a local copy.

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AWS Machine Learning Blog

MARCH 13, 2025

We discuss the unique challenges MaestroQA overcame and how they use AWS to build new features, drive customer insights, and improve operational inefficiencies. They were also able to use the familiar AWS SDK to quickly and effortlessly integrate Amazon Bedrock into their application.

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AWS Machine Learning Blog

FEBRUARY 19, 2025

At AWS re:Invent 2024, we launched a new innovation in Amazon SageMaker HyperPod on Amazon Elastic Kubernetes Service (Amazon EKS) that enables you to run generative AI development tasks on shared accelerated compute resources efficiently and reduce costs by up to 40%.

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Clustering Data Scientist AWS Data Science 84

Pickl AI

MARCH 28, 2025

Popular cloud load balancers like AWS ELB, Google Cloud Load Balancer, and Azure Load Balancer enhance cloud performance. Learning cloud computing and data science through Pickl.AI It balances the load among multiple servers in a cluster, ensuring no single server gets overwhelmed.

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Cloud Computing Algorithm Azure Clustering 52

Hacker News

JULY 1, 2025

Good at Go, Kubernetes (Understanding how to manage stateful services in a multi-cloud environment) We have a Python service in our Recommendation pipeline, so some ML/Data Science knowledge would be good. On the backend we're using 100% Go with AWS primitives. Where you live means something. City vs. Countryside.

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Python AWS ML ML 95

Analytics Vidhya

APRIL 25, 2022

This article was published as a part of the Data Science Blogathon. Introduction Amazon’s Redshift Database is a cloud-based large data warehousing solution. Companies may store petabytes of data in easy-to-access “clusters” that can be searched in parallel using the platform’s storage system.

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Analytics Vidhya

AUGUST 3, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Apache Spark is a framework used in cluster computing environments. The post Building a Data Pipeline with PySpark and AWS appeared first on Analytics Vidhya.

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Data Science 101

NOVEMBER 11, 2019

Welcome to the first beta edition of Cloud Data Science News. This will cover major announcements and news for doing data science in the cloud. Azure Synapse Analytics This is the future of data warehousing. If you are at a University or non-profit, you can ask for cash and/or AWS credits. Microsoft Azure.

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Data Science Dojo

JULY 3, 2024

Data science bootcamps are intensive short-term educational programs designed to equip individuals with the skills needed to enter or advance in the field of data science. They cover a wide range of topics, ranging from Python, R, and statistics to machine learning and data visualization.

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AWS Machine Learning Blog

JULY 15, 2025

Amazon Bedrock Knowledge Bases has extended its vector store options by enabling support for Amazon OpenSearch Service managed clusters, further strengthening its capabilities as a fully managed Retrieval Augmented Generation (RAG) solution. Why use OpenSearch Service Managed Cluster as a vector store?

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Clustering AWS K-nearest Neighbors Database 18

Data Science Dojo

FEBRUARY 20, 2023

It provides a large cluster of clusters on a single machine. Spark is a general-purpose distributed data processing engine that can handle large volumes of data for applications like data analysis, fraud detection, and machine learning. AWS SageMaker also has a CLI for model creation and management.

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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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AWS Machine Learning Blog

JANUARY 24, 2024

We demonstrate how to build an end-to-end RAG application using Cohere’s language models through Amazon Bedrock and a Weaviate vector database on AWS Marketplace. Health Insurance Portability and Accountability Act (HIPAA) eligibility and General Data Protection Regulation (GDPR) compliance.

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Smart Data Collective

MARCH 2, 2022

Data science is a growing profession. Standards and expectations are rapidly changing, especially in regards to the types of technology used to create data science projects. Most data scientists are using some form of DevOps interface these days. Benefits of Kubernetes for Data Science.

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AWS Machine Learning Blog

APRIL 29, 2024

For AWS and Outerbounds customers, the goal is to build a differentiated machine learning and artificial intelligence (ML/AI) system and reliably improve it over time. First, the AWS Trainium accelerator provides a high-performance, cost-effective, and readily available solution for training and fine-tuning large models.

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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.

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AWS Machine Learning Blog

MARCH 15, 2024

The need for federated learning in healthcare Healthcare relies heavily on distributed data sources to make accurate predictions and assessments about patient care. Limiting the available data sources to protect privacy negatively affects result accuracy and, ultimately, the quality of patient care.

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Analytics Vidhya

DECEMBER 30, 2022

This article was published as a part of the Data Science Blogathon. Introduction In machine learning, the data is an essential part of the training of machine learning algorithms. The amount of data and the data quality highly affect the results from the machine learning algorithms.

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AWS Machine Learning Blog

SEPTEMBER 18, 2024

In addition to its groundbreaking AI innovations, Zeta Global has harnessed Amazon Elastic Container Service (Amazon ECS) with AWS Fargate to deploy a multitude of smaller models efficiently. These include dbt pipelines, data gathering jobs, training, evaluation, and batch inference jobs for smaller models.

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AWS Machine Learning Blog

JUNE 11, 2024

Sprinklr’s specialized AI models streamline data processing, gather valuable insights, and enable workflows and analytics at scale to drive better decision-making and productivity. During this journey, we collaborated with our AWS technical account manager and the Graviton software engineering teams.

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Machine Learning Machine Learning AWS Natural Language Processing 120

Analytics Vidhya

MAY 16, 2022

This article was published as a part of the Data Science Blogathon. Introduction on Amazon Elasticsearch Service Amazon Elasticsearch Service is a powerful tool that allows you to perform a number of functions. Let us examine how this powerful tool works behind the scenes.

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AWS Machine Learning Blog

MAY 23, 2023

In April 2023, AWS unveiled Amazon Bedrock , which provides a way to build generative AI-powered apps via pre-trained models from startups including AI21 Labs , Anthropic , and Stability AI. Amazon Bedrock also offers access to Titan foundation models, a family of models trained in-house by AWS. Deploy the AWS CDK application.

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AWS Machine Learning Blog

AUGUST 21, 2023

You can streamline the process of feature engineering and data preparation with SageMaker Data Wrangler and finish each stage of the data preparation workflow (including data selection, purification, exploration, visualization, and processing at scale) within a single visual interface.

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AWS Machine Learning Blog

SEPTEMBER 3, 2024

By using the Livy REST APIs , SageMaker Studio users can also extend their interactive analytics workflows beyond just notebook-based scenarios, enabling a more comprehensive and streamlined data science experience within the Amazon SageMaker ecosystem. This same interface is also used for provisioning EMR clusters.

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AWS Machine Learning Blog

MAY 30, 2024

In this post, we introduce the Media Analysis and Policy Evaluation solution, which uses AWS AI and generative AI services to provide a framework to streamline video extraction and evaluation processes. This solution, powered by AWS AI and generative AI services, meets these needs.

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Flipboard

JULY 22, 2025

Data science teams working with artificial intelligence and machine learning (AI/ML) face a growing challenge as models become more complex. Provided at no additional cost, the DLCs come pre-packaged with CUDA libraries, popular ML frameworks, and the Elastic Fabric Adapter (EFA) plug-in for distributed training and inference on AWS.

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