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Why use AWS Machine Learning?
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.
For developers with no prior machine learning experience, AWS offers a suite of AI services to easily build sophisticated AI-driven applications, such as personalized recommendations, contact centers, live media subtitling, and automated document analysis - often building on AI technology used to power Amazon’s own businesses. For machine learning developers and data scientists Amazon SageMaker is a fully managed ML service to quickly build, train, and deploy ML models at scale. Expert practitioners can develop on the framework of their choice as a managed experience in Amazon SageMaker or use the AWS Deep Learning AMIs (Amazon machine images) which are fully configured with the latest versions of the most popular deep learning framework and tools.
AWS Machine Learning Customers
From the world’s largest enterprises to emerging start-ups, more ML is built on AWS than anywhere else.
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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. Learn more »
AWS AI Services - Easily add intelligence to applications. No machine learning skills required.
Pre-trained 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. Explore all AWS AI services »
AWS AI Services
With AI Services from AWS, you can add capabilities like image and video analysis, forecasting, personalized recommendations, virtual assistants, and document analysis to your applications without ML expertise. For instance, developers can automatically extract text and data from millions of documents in just hours using Amazon Textract.
Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy ML models quickly. SageMaker removes the heavy lifting from each step of the ML process to make it easier to develop high quality models. Traditional ML development is a complex, expensive, iterative process made even harder because there are no integrated tools for the entire ML workflow. You need to stitch together tools and workflows, which is time-consuming and error-prone. SageMaker solves this challenge by providing all of the components used for machine learning in a single toolset so models get to production faster with much less effort and at lower cost.
AWS Educational Devices
AWS offers a portfolio of educational devices designed for developers of all skill levels to learn the fundamentals of ML in fun, practical ways. Check out the videos below to see AWS DeepRacer and AWS DeepLens in action:
AWS Training and Certification
Dive deep into the same ML curriculum used to train Amazon’s developers and data scientists. Developers, data scientists, data platform engineers, and business decision makers can use this training to learn how to apply ML, AI, and deep learning to their businesses unlocking new insights and value. Pick a role-based learning path »
Tutorials and Labs
Hands-on tutorials to help you get started with AWS ML quickly. View all tutorials »
AWS Architecture Center
Visit the Machine Learning category of the AWS Architecture Center to learn best practices for building optimal Machine Learning architectures.