Putting machine learning in the hands of every developer.
AWS offers the broadest and deepest set of machine learning services and supporting cloud infrastructure, putting machine learning in the hands of every developer, data scientist and expert practitioner. AWS is helping more than one hundred thousand customers accelerate their machine learning journey.
Explore machine learning services that fit your business needs, and learn how to get started.
Explore AWS Machine Learning services
Amazon SageMaker – Build, train, and deploy machine learning models fast
Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy ML models at scale. It removes the complexity from each step of the ML workflow so you can more easily deploy your ML use cases, anything from predictive maintenance to computer vision to predicting customer behaviors.
AI Services – Easily add intelligence to applications. No machine learning skills required
AI Services provide ready-made intelligence for your applications and workflows to help you improve business outcomes – based on the same technology used to power Amazon’s own businesses. You can build AI-powered applications without any machine learning expertise.
Industrial
From detecting abnormal machine behavior with sensor data to improving operations with computer vision, these purpose-built AI services help industrial customers transform their business – no machine learning experience required.
Healthcare
HIPAA-eligible services that use machine learning to unlock the potential of health data.
Machine Learning Infrastructure – scalable, high performance, and cost-effective
AWS provides the broadest and deepest portfolio of ML infrastructure services with a choice of processors and accelerators to meet your unique performance and budget needs. Amazon EC2 P4d instances provide the highest performance for ML training in the cloud with the latest NVIDIA A100 Tensor Core GPUs coupled with first in the cloud 400 Gbps instance networking. P4d instances are deployed in hyper scale clusters, called EC2 UltraClusters, offering supercomputer-class performance for the most complex ML training jobs. For inference, Amazon EC2 Inf1 instances, powered by AWS Inferentia chips, provide high performance and lowest cost inference in the cloud
Machine Learning frameworks and libraries – Choice of frameworks and toolkits, optimized for AWS
Choose from TensorFlow, PyTorch, Apache MXNet, and other popular frameworks to experiment with and customize machine learning algorithms. You can use the framework of your choice as a managed experience in Amazon SageMaker or use the AWS Deep Learning AMIs and Deep Learning Containers, which are fully configured with the latest versions of the most popular deep learning frameworks and open source toolkits, optimized for performance on the AWS network and infrastructure. For example, Amazon SageMaker now provides an optimized Hugging Face transformers library providing 38% performance improvement over the open source implementation.
Learning tools – Get hands-on with machine learning
Explore the portfolio of educational devices designed for developers of all skill levels to learn the fundamentals of machine learning in fun, practical ways.
BRAMS Partnership with the leader
With its expertise, BRAMS offers you market-leading cloud solutions billed per use. With BRAMS, now you can unleash your full potential and focus on what matters most: Your activities. Thanks to its partnerships and collaboration with the biggest global cloud pioneers: Microsoft, Amazon Web Services, IBM Cloud and Google Cloud, Brams has become a multi-industry focus, to support companies of different sectors and sizes to move to the Cloud for more than two decades of expertise.
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Source: https://aws.amazon.com/machine-learning/?nc2=h_ql_prod_ml
