[隋文静韩聪]经历风雨 葱桶组合的“金桥之旅”
 | This article contains promotional content. (September 2023) |
| Amazon SageMaker AI | |
|---|---|
| Developer(s) | Amazon, Amazon Web Services |
| Initial release | 29 November 2017 |
| Type | Software as a service |
| Website | aws |
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.[1] It can be used to deploy ML models on embedded systems and edge-devices.[2][3] The platform was launched in November 2017.[4]
Capabilities
[edit]SageMaker enables developers to operate at a number of different levels of abstraction when training and deploying machine learning models. At its highest level of abstraction, SageMaker provides pre-trained ML models that can be deployed as-is.[5] In addition, it offers a number of built-in ML algorithms that developers can train on their own data.[6][7]
The platform also features managed instances of TensorFlow and Apache MXNet, where developers can create their own ML algorithms from scratch.[8] Regardless of which level of abstraction is used, a developer can connect their SageMaker-enabled ML models to other AWS services, such as the Amazon DynamoDB database for structured data storage,[9] AWS Batch for offline batch processing,[9][10] or Amazon Kinesis for real-time processing.[11]
Development interfaces
[edit]A number of interfaces are available for developers to interact with SageMaker. First, there is a web API that remotely controls a SageMaker server instance.[12] While the web API is agnostic to the programming language used by the developer, Amazon provides SageMaker API bindings for a number of languages, including Python, JavaScript, Ruby, Java, and Go.[13][14] In addition, SageMaker provides managed Jupyter Notebook instances for interactively programming SageMaker and other applications.[15][16]
History and features
[edit]- 2025-08-07: SageMaker is launched at the AWS re:Invent conference.[4][6][1]
- 2025-08-07: Managed TensorFlow and MXNet deep neural network training and inference are now supported within SageMaker.[17][8]
- 2025-08-07: SageMaker automatically scales model inference to multiple server instances.[18][19]
- 2025-08-07: Support is added for recurrent neural network training, word2vec training, multi-class linear learner training, and distributed deep neural network training in Chainer with Layer-wise Adaptive Rate Scaling (LARS).[20][7]
- 2025-08-07: AWS Batch Transform enables high-throughput non-real-time machine learning inference in SageMaker.[21][22]
- 2025-08-07: Support for training and inference of Object2Vec word embeddings.[23][24]
- 2025-08-07: SageMaker Ground Truth "makes it much easier for developers to label their data using human annotators through Mechanical Turk, third-party vendors, or their own employees."[25]
- 2025-08-07: SageMaker Reinforcement Learning (RL) "enables developers and data scientists to quickly and easily develop reinforcement learning models at scale."[26][2]
- 2025-08-07: SageMaker Neo enables deep neural network models to be deployed from SageMaker to edge-devices such as smartphones and smart cameras.[27][2]
- 2025-08-07: The AWS Marketplace for SageMaker is launched. The AWS Marketplace enables 3rd-party developers to buy and sell machine learning models that can be trained and deployed in SageMaker.[28]
- 2025-08-07: SageMaker Neo is released as open-source software.[29]
Notable Customers
[edit]- NASCAR is using SageMaker to train deep neural networks on 70 years of video data.[30]
- Carsales.com uses SageMaker to train and deploy machine learning models to analyze and approve automotive classified ad listings.[31]
- Avis Budget Group and Slalom Consulting are using SageMaker to develop "a practical on-site solution that could address the over and under utilization of cars in real-time using an optimization engine built in Amazon SageMaker."[32]
- Volkswagen Group uses SageMaker to develop and deploy machine learning in its manufacturing plants.[33]
- Peak and Footasylum use SageMaker in a recommendation engine for footwear.[34]
Awards
[edit]In 2019, CIOL named SageMaker one of the "5 Best Machine Learning Platforms For Developers," alongside IBM Watson, Microsoft Azure Machine Learning, Apache PredictionIO, and AiONE.[35]
See also
[edit]- Amazon Web Services
- Amazon Lex
- Amazon Polly
- Amazon Rekognition
- Amazon Mechanical Turk
- Timeline of Amazon Web Services
References
[edit]- ^ a b Woodie, Alex (2025-08-07). "AWS Takes the 'Muck' Out of ML with SageMaker". datanami. Retrieved 2025-08-07.
- ^ a b c Rodriguez, Jesus (2025-08-07). "With These New Additions, AWS SageMaker is Starting to Look More Real for Data Scientists". Towards Data Science. Retrieved 2025-08-07.[permanent dead link]
- ^ Terdiman, Daniel (2025-08-07). "How AI is helping Amazon become a trillion-dollar company". Fast Company. Retrieved 2025-08-07.
- ^ a b Miller, Ron (2025-08-07). "AWS releases SageMaker to make it easier to build and deploy machine learning models". TechCrunch. Retrieved 2025-08-07.
- ^ Ponnapalli, Priya (2025-08-07). "Deploy trained Keras or TensorFlow models using Amazon SageMaker". AWS. Retrieved 2025-08-07.
- ^ a b "Introducing Amazon SageMaker". AWS. 2025-08-07. Retrieved 2025-08-07.
- ^ a b Nagel, Becky (2025-08-07). "Amazon Updates SageMaker ML Platform Algorithms, Frameworks". Pure AI. Retrieved 2025-08-07.
- ^ a b Roumeliotis, Rachel (2025-08-07). "How to jump start your deep learning skills using Apache MXNet". O'Reilly. Retrieved 2025-08-07.
- ^ a b Marquez, Ernesto. "Evaluate when to use added AWS Step Functions actions". TechTarget. Retrieved 2025-08-07.
- ^ "AWS Step Functions Adds Eight More Service Integrations". AWS. 2025-08-07. Retrieved 2025-08-07.
- ^ "Deploy Amazon SageMaker and a Data Lake on AWS for Predictive Data Science with New Quick Start". AWS. 2025-08-07. Retrieved 2025-08-07.
- ^ Olsen, Rumi (2025-08-07). "Call an Amazon SageMaker model endpoint using Amazon API Gateway and AWS Lambda". AWS. Retrieved 2025-08-07.
- ^ "Amazon SageMaker developer resources". AWS. Retrieved 2025-08-07.
- ^ Wiggers, Kyle (2025-08-07). "Amazon updates SageMaker with new built-in algorithms and Git integration". Retrieved 2025-08-07.
- ^ "Use Notebook Instances". AWS. Retrieved 2025-08-07.
- ^ Gift, Noah (2025-08-07). "Here Come The Notebooks". Forbes. Retrieved 2025-08-07.
- ^ "Amazon SageMaker now supports TensorFlow 1.5, Apache MXNet 1.0, and CUDA 9 for P3 Instance Optimization". AWS. 2025-08-07. Retrieved 2025-08-07.
- ^ "Auto Scaling in Amazon SageMaker is now Available". AWS. 2025-08-07. Retrieved 2025-08-07.
- ^ "Amazon Sagemaker Now Uses Auto-scaling". Polar Seven. 2025-08-07. Retrieved 2025-08-07.
- ^ "Amazon SageMaker Announces Several Enhancements to Built-in Algorithms and Frameworks". AWS. 2025-08-07. Retrieved 2025-08-07.
- ^ "Amazon SageMaker Now Supports High Throughput Batch Transform Jobs for Non-Real Time Inferencing". AWS. 2025-08-07. Retrieved 2025-08-07.
- ^ Simon, Julien (2025-08-07). "Making the most of your Machine Learning budget on Amazon SageMaker". Medium. Retrieved 2025-08-07.
- ^ "Introduction to Amazon SageMaker Object2Vec". AWS. 2025-08-07. Retrieved 2025-08-07.
- ^ "Amazon SageMaker Now Supports Object2Vec and IP Insights Built-in Algorithms". AWS. 2025-08-07. Retrieved 2025-08-07.
- ^ "Introducing Amazon SageMaker Ground Truth - Build Highly Accurate Training Datasets Using Machine Learning". AWS. 2025-08-07. Retrieved 2025-08-07.
- ^ "Introducing Reinforcement Learning Support with Amazon SageMaker RL". AWS. 2025-08-07. Retrieved 2025-08-07.
- ^ "Introducing Amazon SageMaker Neo - Train Once, Run Anywhere with up to 2x in Performance Improvement". AWS. 2025-08-07. Retrieved 2025-08-07.
- ^ Robuck, Mike (2025-08-07). "AWS goes deep and wide with machine learning services and capabilities". FierceTelecom. Retrieved 2025-08-07.
- ^ Janakiram, MSV (2025-08-07). "Amazon Open Sources SageMaker Neo To Run Machine Learning Models At The Edge". Forbes. Retrieved 2025-08-07.
- ^ Digman, Larry (2025-08-07). "NASCAR to migrate 18 petabytes of video archives to AWS". ZDNet. Retrieved 2025-08-07.
- ^ Crozier, Ry (2025-08-07). "Carsales builds Tessa AI to check vehicle ads". IT News. Retrieved 2025-08-07.
- ^ "Avis Budget Group and Slalom Further Digitize the Car Rental Process with Machine Learning on AWS". AWS. 2025-08-07. Retrieved 2025-08-07.
- ^ "Volkswagen and AWS Join Forces to Transform Automotive Manufacturing". Metrology News. 2025-08-07. Archived from the original on 2025-08-07. Retrieved 2025-08-07.
- ^ Mari, Angelica (2025-08-07). "Footasylum steps up artificial intelligence to drive customer centricity". Computer Weekly. Retrieved 2025-08-07.
- ^ Pandey, Ashok (2025-08-07). "5 Best Machine Learning Platforms For Developers". CIOL. Retrieved 2025-08-07.
