Introduction

Beginner | 5 minutes

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.

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 »

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Amazon SageMaker Studio
SageMaker Studio is the first fully integrated development environment for ML, to build, train, and deploy ML models at scale
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Amazon SageMaker Ground Truth
SageMaker Ground Truth provides pre-built workflows and interfaces to build and manage highly accurate training datasets quickly
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Amazon SageMaker Autopilot
SageMaker Autopilot is the industry's first automated ML capability that gives you complete visibility into your ML models
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Amazon SageMaker Neo
SageMaker Neo enables developers to train ML models once and run them anywhere in the cloud and at the edge

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 »

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Amazon CodeGuru
Automate code reviews and identify your most expensive lines of code
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Amazon Transcribe
Easily add high-quality speech-to-text capabilities to your applications and workflows
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Amazon Comprehend
Use natural language processing to extract insights and relationships from unstructured text
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Amazon Forecast
Build accurate forecasting models based on the same ML forecasting technology used by Amazon.com
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Amazon Rekognition
Add image and video anaylysis to your applications to catalog assets, automate media workflows, and extract meaning
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Amazon Textract
Automatically extract text and data from millions of documents in just hours, reducing manual efforts
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Amazon Polly
Turn text into life-like speech to give voice to your applicaitons
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Amazon Lex
Easily build conversational agents to improve customer service and increase contact center efficiency
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Amazon Personalize
Personalize experiences for your customers using ML technology perfected from years of use on Amazon.com
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Amazon Kendra
Add natural language search capabilities to your apps so users can find the information they need more easily
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Amazon Fraud Detector
Identify potentially fraudulent online activities based on the same technology used by Amazon.com
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Amazon Translate
Expand your reach through efficient and cost-effective translation to reach audiences in multiple languages

Fundamentals

Beginner | 10 minutes

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.

What is Amazon Textract?

Amazon SageMaker

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.

What is Amazon SageMaker?

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:

Get Rolling with ML
How Machine Learning Kept Out the Cat

Learning Resources

Beginner | 30 minutes

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 »

Introduction to AWS Machine Learning Services
This course introduces Amazon ML and AI tools that enable capabilities across frameworks and infrastructure, machine learning platforms, and API-driven services. To do ML well, you need competencies across these key layers, the right data store, security, and resources for analytics.
Start the course »
Machine Learning Terminology and Process
This course introduces you to basic ML concepts and the machine process the data goes through. We explore each step in the machine learning process in detail and explain some of the common terms and techniques that occur during a phase of a ML project.
Start the course »
AWS Foundations: Machine Learning Basics
What is ML? How can ML solve business problems? When is it appropriate to use a ML model? What are the phases of a ML pipeline? In this course, you get an overview of the concepts, terminology, and processes of the exciting field of ML!
Start the course »

Tutorials and Labs

Hands-on tutorials to help you get started with AWS ML quickly. View all tutorials »

Build, Train, and Deploy a ML model with Amazon SageMaker
In this tutorial, you will learn how to use Amazon SageMaker to build, train, and deploy a ML model. We will use the popular XGBoost ML algorithm for this exercise. Amazon SageMaker is a modular, fully managed ML service that enables developers and data scientists to build, train, and deploy ML models at scale.
Start the tutorial »
Create a machine learning model automatically with Amazon SageMaker Autopilot
In this tutorial, you create ML models automatically without writing a line of code! You use Amazon SageMaker Autopilot, an AutoML capability that automatically creates the best classification and regression ML models, while allowing full control and visibility.
Start the tutorial »

Additional Resources

SageMaker Fridays

Join our subject matter experts on SageMaker Fridays, a live show on Twitch to get you started faster with machine learning. Each episode will covers an aspect of the ML workflow with an interactive session and live coding.
View all SageMaker Fridays »

Online Tech Talks

Join us for online presentations led by AWS solutions architects and engineers covering a range of ML topics and expertise levels.
View all Online Tech Talks »

AWS Summits

Coming to a city near you! Attend technical breakout sessions, demonstrations, workshops, and even race on the AWS DeepRacer tracks.
Find an AWS Summit near you »