Amazon Web Services
aws.amazon.com › products › analytics › amazon sagemaker
The center for all your data, analytics, and AI – Amazon SageMaker – AWS
1 week ago - Build, train, and deploy ML and FMs with fully managed infrastructure, tools, and workflows with Amazon SageMaker AI ... Analyze, prepare, and integrate data for analytics and AI using open source frameworks on Amazon Athena, Amazon EMR, and AWS Glue
Factsheet
Amazon SageMaker AI
Developers Amazon, Amazon Web Services
Initial release 29 November 2017; 8 years ago (2017-11-29)
Amazon SageMaker AI
Developers Amazon, Amazon Web Services
Initial release 29 November 2017; 8 years ago (2017-11-29)
Wikipedia
en.wikipedia.org › wiki › Amazon_SageMaker
Amazon SageMaker - Wikipedia
October 12, 2025 - Amazon SageMaker AI is a cloud-based machine-learning platform that allows the creation, training, and deployment by developers of machine-learning (ML) models on the cloud. It can be used to deploy ML models on embedded systems and edge-devices. The platform was launched in November 2017.
Amazon SageMaker -- What an absolute ripoff!
at least 10 years experience in IT to set it up Think about it this way. AWS was designed primarily with one customer in mind. Amazon. It's not really designed for students, hobbyists, or companies small enough that $300 is an expensive lesson. More on reddit.com
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October 3, 2023Sagemaker makes me hate my job
Don't use Sagemaker if you can avoid it. It does not do anything you can't do with open source libraries. The reason Sagemaker (and similar services like Azure ML) exist is to bill you extra for the same computational resources you could get without it. That's literally it. Also this way cloud companies try to vendor lock-in you and your team More on reddit.com
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May 29, 2024Newbie trying to understand sagemaker/aws and LLMs
Bedrock is still private, it should meet pretty much any compliance in terms of data stewardship. For example, it is even HIPAA compliant. You should speak with your AWS Technical Account Manager about this, they can provide info and make sure you are operating within whatever compliance you require. I highly suggest going that way because it doesn't sound like you have the experience necessary to jump right into SageMaker or EC2. You can get there, but it's much better to start with a fully hosted solution. More on reddit.com
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February 25, 2024Why not Sagemaker?
Con: Bloody expensive More on reddit.com
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April 5, 2023Videos
57:35
Sagemaker Your All-in-One Data and AI Platform - Lets Talk About ...
02:57
Getting started with Amazon SageMaker Studio | Amazon Web Services ...
SageMaker Studio: ML Development Overview - AWS
09:01
Amazon SageMaker overview | Amazon Web Services - YouTube
03:55:29
AI Engineering with AWS SageMaker: Crash Course for Beginners! ...
01:55
Introduction to SageMaker AI | Amazon Web Services - YouTube
AWS
docs.aws.amazon.com › aws prescriptive guidance › image classification solutions on aws › building an image classification model › training an image classification model › amazon sagemaker ai endpoints
Amazon SageMaker AI endpoints - AWS Prescriptive Guidance
DocumentationAWS Prescriptive GuidanceImage classification solutions on AWS · Amazon SageMaker AI is a managed ML service that helps you build and train models and then deploy them into a production-ready hosted environment. Unlike Amazon SageMaker AI Canvas, you don't have the option of using ...
IBM
ibm.com › think › topics › amazon-sagemaker
What Is Amazon SageMaker? | IBM
November 17, 2025 - Amazon SageMaker is a fully managed service designed to simplify the process of building, training and deploying machine learning (ML) models. Created by Amazon Web Services (AWS), SageMaker automates many of the labor-intensive tasks involved ...
AWS
aws.amazon.com › blogs › machine-learning
Artificial Intelligence
1 day ago - In this post, we share how dLocal worked closely with the AWS team to help shape the product roadmap, reinforce its role as an industry innovator, and set new benchmarks for operational excellence in the global fintech landscape. In this post, we explore how Qbtech streamlined their machine learning (ML) workflow using Amazon SageMaker AI, a fully managed service to build, train and deploy ML models, and AWS Glue, a serverless service that makes data integration simpler, faster, and more cost effective.
GeeksforGeeks
geeksforgeeks.org › machine learning › what-is-sagemaker-in-aws
What is SageMaker in AWS? - GeeksforGeeks
1 week ago - The platform provides a suite of ML modeling tools within an easy-to-use framework. With SageMaker templates, businesses can quickly build, train, host, and deploy machine learning models at scale in the AWS cloud.
AWS
aws.amazon.com › about-aws › whats-new › 2025 › 12 › amazon-sagemaker-nbi-soci
Amazon SageMaker Studio now supports SOCI indexing for faster container startup times - AWS
6 days ago - Today, AWS announces SOCI (Seekable Open Container Initiative) indexing support for Amazon SageMaker Studio, reducing container startup times by 30-50% when using custom images. Amazon SageMaker Studio is a fully integrated, browser-based environment for end-to-end machine learning development.
DataCamp
datacamp.com › tutorial › aws-sagemaker-tutorial
The Complete Guide to Machine Learning on AWS with Amazon SageMaker | DataCamp
June 19, 2024 - Discover how Amazon SageMaker simplifies machine learning workflows. Learn about building, training, and deploying models on AWS with this fully managed service.
Amazon Web Services
amazonaws.cn › home › products › amazon sagemaker
Amazon SageMaker
1 week ago - Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. SageMaker removes the heavy lifting from each step of the machine learning process to make it easier to develop high ...
Saturn Cloud
saturncloud.io › glossary › aws-sagemaker
AWS SageMaker | Saturn Cloud
March 19, 2024 - AWS SageMaker is a managed service provided by Amazon Web Services (AWS) that allows data scientists and developers to build, train, and deploy machine learning models quickly and efficiently.
Reddit
reddit.com › r/aws › amazon sagemaker -- what an absolute ripoff!
r/aws on Reddit: Amazon SageMaker -- What an absolute ripoff!
October 3, 2023 -
If you're new to AWS, run away now! Basically, to use their services, you'll need a PhD in Internet Security or at least 10 years experience in IT to set it up. Then, they have a never ending cascade of help pages. You'll read one and think you can follow it, then it'll send you to one more. It just doesn't stop.
Amazon knows this. So with SageMaker, they lure you in with a push one-button solution. If you push it, you have to remember to turn everything off before exiting. And if you create an "end point", you have to go into a 10 tab side menu entitled "Inferences" to turn it off???? Not intuitive, not user-friendly. $300 dollars later I've learned my lesson. Don't fucking use this service!
It's like you forgot to turn the lights off at you house and you have to pay $20/ per day. Then the utility company came and hid all the light switches to turn it off at your neighbor's house. You didn't realize you were getting charged until your credit card bill showed up at the end of the month.
Take that $600 you're going to get charged and go put it towards a new computer. That's the lesson. Scalability my ass. (my luck this forum is probably moderated by the AWS sales department)
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at least 10 years experience in IT to set it up Think about it this way. AWS was designed primarily with one customer in mind. Amazon. It's not really designed for students, hobbyists, or companies small enough that $300 is an expensive lesson.
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Ignored ubiquitous good practice advice to setup a billing alarm? Didn’t read the pricing page? It’s on you.
TechTarget
techtarget.com › searchaws › definition › Amazon-SageMaker
What is Amazon SageMaker?
Software capabilities are abstracted in intuitive SageMaker templates. They provide a framework to build, host, train and deploy ML models at scale in the Amazon public cloud. See how training and inference are used in developing and updating machine learning models. AWS SageMaker simplifies ML modeling into three steps: preparation, training and deployment.
Amazon Web Services
aws.amazon.com › artificial intelligence › machine learning
Machine Learning (ML) on AWS - ML Models and Tools - AWS
1 week ago - From the world’s largest enterprises to emerging startups, more than 100,000 customers have chosen AWS machine learning services to solve business problems and drive innovation. With SageMaker AI, you can build, train, and deploy machine learning and foundation models at scale with infrastructure and purpose-built tools for each step of the ML lifecycle.
XenonStack
xenonstack.com › amazon-web-services › amazon-sagemaker
AWS AI and Machine learning Services with Sagemaker
Ensure compliance with security standards and regulations to enhance data security across AWS services. ... Optimize scalability and resource management while simplifying operations for enterprise workloads. ... Consolidate and analyze vast data volumes to derive actionable insights and drive strategic decision-making. ... Utilize SageMaker to seamlessly scale AI and ML model development, training, and deployment on AWS.
DEV Community
dev.to › aws-builders › from-raw-clinical-data-to-ai-building-a-modern-healthcare-data-platform-on-aws-1mi7
From Raw Clinical Data to AI: Building a Modern Healthcare Data Platform on AWS - DEV Community
2 weeks ago - To process clinical notes and other unstructured data, we need to incorporate NLP techniques that allow extracting entities, mapping clinical concepts and automatically encoding information. For this type of processing, we can rely on the following AWS services: Amazon SageMaker Allows training, tuning and deploying custom NLP models, from classic models to advanced transformer-based ones.
Business Wire
businesswire.com › news › home › 20251201236344 › en › AWS-Powers-Sonys-Enterprise-AI-and-Engagement-Platforms
AWS Powers Sony's Enterprise AI and Engagement Platforms
3 weeks ago - (AWS), an Amazon.com, Inc. company (NASDAQ: AMZN), today announced new Amazon Bedrock and Amazon SageMaker AI capabilities: Reinforcement Fine Tuning (RFT) in Amazon Bedrock and serverless model customization in Amazon SageMaker AI with reinforcement learning.
NVIDIA Blog
blogs.nvidia.com › home › nvidia and aws expand full-stack partnership, providing the secure, high-performance compute platform vital for future innovation
NVIDIA and AWS Expand Full-Stack Partnership, Providing the Secure, High-Performance Compute Platform Vital for Future Innovation
3 weeks ago - This expanded support builds on AWS’s existing integrations with NVIDIA technologies — including NVIDIA NIM microservices and frameworks like NVIDIA Riva and NVIDIA BioNeMo, as well as model development tools integrated with Amazon SageMaker and Amazon Bedrock — that enable organizations to deploy agentic AI, speech AI and scientific applications faster than ever.
DEV Community
dev.to › kazuya_dev › aws-reinvent-2025-scale-ai-agents-with-custom-models-using-amazon-sagemaker-ai-sglang-aim387-2n6
AWS re:Invent 2025 - Scale AI agents with custom models using Amazon SageMaker AI & SGLang (AIM387) - DEV Community
2 weeks ago - In this video, AWS demonstrates building production-ready agentic AI applications using Amazon SageMaker's end-to-end capabilities. The session covers fine-tuning Llama 3.2 3B with QLoRA on medical data, deploying models using custom SGLang containers via SageMaker's BYOC paradigm, and orchestrating workflows with SageMaker Pipelines.
Siliconvalleycloudit
siliconvalleycloudit.com › home › introduction to aws sagemaker
Introduction to AWS SageMaker | Silicon Valley Cloud IT
June 7, 2023 - We need to create a machine learning model to predict the cost of cars, data containing a number of models, details to predict sale prices; all this data can be put into a CSV file and then drop into an Amazon S3 bucket. Then the user can launch SageMaker autopilot and spin up models with different algorithms, datasets, and parameters.
Medium
medium.com › swlh › a-gentle-introduction-to-aws-sagemaker-ml-ai-on-the-cloud-de8dd0191818
A Gentle Introduction to AWS SageMaker — ML & AI on the Cloud | by Jacky Zou | The Startup | Medium
July 23, 2020 - A Gentle Introduction to AWS SageMaker — ML & AI on the Cloud Making Machine Learning model building & deployment in live production a seamless experience for both Software Engineers and Data …