Machine Learning on AWS

Putting machine learning in the hands of every developer

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On behalf of our customers, we are focused on solving some of the toughest challenges that hold back machine learning from being in the hands of every developer.

You can choose from pre-trained AI services for computer vision, language, recommendations, and forecasting; Amazon SageMaker to quickly build, train and deploy machine learning models at scale; or build custom models with support for all the popular open-source frameworks.

Our capabilities are built on the most comprehensive cloud platform, optimized for machine learning with high-performance compute, and no compromises on security and analytics.

Expedia Group

"AWS is our ML platform of choice, unlocking new ways to deliver on our promise of being the world’s travel platform."

--Matthew Fryer, Hotels.com Vice President and Chief Data Science Officer, Expedia Group

Tens of thousands of customers

More machine learning happens on AWS than anywhere else.

AWS Machine Learning Customers

ML Services
ML Services

Build, train, and deploy ML fast

AI Services
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Easily add intelligence to your applications

Frameworks
Frameworks

Choice and flexibility with broadest framework support

Compute
Compute

Fastest and lowest-cost compute options

Analytics and Security
Analytics and Security

Comprehensive capabilities, no compromise

Learning Tools
Learning Tools

Get deep on ML with AWS DeepRacer and DeepLens

ML SERVICES

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Build, train, and deploy machine learning models fast

Amazon SageMaker enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. It removes the complexity that gets in the way of successfully implementing machine learning across use cases and industries—from running models for real-time fraud detection, to virtually analyzing biological impacts of potential drugs, to predicting stolen-base success in baseball.

Amazon SageMaker Studio:Experience the first fully integrated development environment (IDE) for machine learning with Amazon SageMaker Studio, where you can perform all ML development steps. You can quickly upload data, create and share new notebooks, train and tune ML models, move back and forth between steps to adjust experiments, debug and compare results, and deploy and monitor ML models all in a single visual interface, making you much more productive.

Amazon SageMaker Autopilot:Automatically build, train, and tune models with full visibility and control, using Amazon SageMaker Autopilot. It is the industry’s first automated machine learning capability that gives you complete control and visibility into how your models were created and what logic was used in creating these models.

BUILD


Collaborate faster with Amazon SageMaker Notebooks:Now available in preview, Amazon SageMaker Notebooks provide one-click Jupyter notebooks that you can start working within seconds. Sharing is easy since all code dependencies are automatically captured, so you can easily collaborate with others. Built-in algorithms and deep learning frameworks: Use built-in algorithms and leading deep learning frameworks that have been optimized for scale, accuracy, and performance.

ML marketplace:Choose from hundreds of pre-built algorithms and model available in AWS Marketplace for Machine Learning and use them in Amazon SageMaker.

Reduce labeling costs by up to 70%:Build highly accurate training datasets and reduce data labeling costs by up to 70% using Amazon SageMaker Ground Truth.

TRAIN


One-click training with accuracy:Train your models on a fully managed infrastructure with a single click or by making a single API call. Get maximum accuracy with automatic model tuning to select the best combinations of the hyperparameters from your chosen algorithms.

Experiment management:Organize, track, evaluate, and compare thousands of training runs with Amazon SageMaker Experiments. You can track and manage iterations as the input parameters, configurations, and results are automatically captured allowing you to organize and evaluate many experiments.

Analyze, debug, and fix problems: Amazon SageMaker Debugger removes the opaqueness from the ML training process by automatically capturing real-time metrics during allowing you to improve model accuracy.

DEPLOY


One-click deployment:Deploy your trained ML models with a single click or a single API call to start generating predictions for real-time or batch data.

Keep models accurate over time:Use Amazon SageMaker Model Monitor to detect and remediate concept drift, and maintain high quality for your deployed ML models.

Lower machine learning inference costs by up to 75%:Use Amazon Elastic Inference to attach just the right amount of GPU-powered inference acceleration with no code changes, helping you to reduce inference costs by up to 75%.

Easier orchestration with SageMaker Operators for Kubernetes:Use the fully managed capabilities of Amazon SageMaker for your ML infrastructure, and continue to use Kubernetes for orchestration and better control for managing your pipelines.

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GE Healthcare
Hotels.com
NFL
Intuit
Thomson Reuters
Dow Jones

AI SERVICES

Easily add intelligence to applications

No machine learning skills required

AWS pre-trained AI Services provide ready-made intelligence for your applications and workflows. AI Services easily integrate with your applications to address common use cases such as personalized recommendations, modernizing your contact center, improving safety and security, and increasing customer engagement. Because we use the same deep learning technology that powers Amazon.com and our ML Services, you get quality and accuracy from continuously-learning APIs. And best of all, AI Services on AWS don't require machine learning experience.

Recommendations

Recommendations

Personalize experiences for your customers with the same recommendation technology used at Amazon.com.

Forecasting

Forecasting

Build accurate forecasting models based on the same machine learning forecasting technology used by Amazon.com.

Image and Video Analysis

Image and Video Analysis

Add image and video analysis to your applications to catalog assets, automate media workflows, and extract meaning.

Advanced Text Analytics

Advanced Text Analytics

Use natural language processing to extract insights and relationships from unstructured text.

Document Analysis

Document Analysis

Automatically extract text and data from millions of documents in just hours, reducing manual efforts.

Voice

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Turn text into lifelike speech to give voice to your applications.

Conversational Agents

Conversational Agents

Easily build conversational agents to improve customer service and increase contact center efficiency.

Translation

Translation

Expand your reach through efficient and cost-effective translation to reach audiences in multiple languages.

Transcription

Transcription

Easily add high-quality speech-to-text capabilities to your applications and workflows.

Conversational Agents

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Translation

Fraud Detection

Identify potentially fraudulent online activities based on the same technology used at Amazon.com.

Transcription

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Automate code reviews and identify your most expensive lines of code.

Motorola Solutions
Duolingo
Finra
Vidmob
NASA
GE Appliances

ML FRAMEWORKS

Choice and flexibility with ML frameworks

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 (Amazon machine images), which are fully configured with the latest versions of the most popular deep learning frameworks and tools.

  • 81% of deep learning projects in the cloud run on AWS
  • 85% of TensorFlow projectsin the cloud run on AWS
  • Fastest training for popular deep learning models:AWS-optimized TensorFlow and PyTorch recorded the fastest training time for Mask-RCNN (object detection) and BERT (natural language processing). Learn more »

85%

of TensorFlow projects in the cloud happen on AWS

Zendesk
News Corp Australia
Hudl
Snapchat
Celgene
Siemens

COMPUTE

Get the right compute for any use case

Leverage a broad set of powerful compute options, ranging from GPUs for compute-intensive deep learning, to FPGAs for specialized hardware acceleration, to high-memory instances for running inference. Amazon EC2 provides a wide selection of instance types optimized to fit machine learning use cases, whether you are training models or running inference on trained models.

  • 3x faster network throughputthan other providers using P3dn instances
  • 25% improvement in price and performanceusing C5 instances powered by 3.0GHz Intel Xeon compared to previous generation instances
  • Custom hardware accelerationusing F1 instances with field programmable gate arrays (FPGAs)
  • High performance and the lowest cost machine learning inferencein the cloud with Inf1 instances

ANALYTICS & SECURITY

Analytics and security for machine learning

In order to do machine learning successfully, you not only need machine learning capabilities, but also the right security, data store, and analytics services to work together.With AWS, you get the most comprehensive capabilities to support your machine learning workloads.

  • 99.999999999% durability and unmatched availabilityusing Amazon S3 and Amazon S3 Glacier for storage
  • Up to 400% faster data queriesusing Amazon Redshift for analytics
  • Deepest set of security & encryptioncapabilities

STORAGE| AmazonS3

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SECURITY| AWS Security

LEARNING TOOLS

The keys to machine learning

AWS DeepComposer

Get started by using the MIDI-compatible AWS DeepComposer keyboard to compose melodies as input for your ML generated compositions.

  • Explore the pre-trained sample models available in the AWS DeepComposer console, or build your own custom GAN architecture in Amazon Sagemaker, to create original and inspiring music
  • Get creative and customize your AI-generated music using your favorite Digital Audio Workstation (DAW).
  • Upload your finished AI-generated compositions directly from AWS DeepComposer into SoundCloud to share your tracks with the world.

AWS DeepRacer Autonomous Race Car
AWS DeepRacer Autonomous Race Car

Get deep with machine learning

AWS DeepRacer

AWS DeepRacer is a fully autonomous 1/18th-scale race car designed to help you learn about reinforcement learning through autonomous driving.

  • Experience the thrill of the race in the real world when you deploy your RL model onto AWS DeepRacer
    • Build models in Amazon SageMaker and then train, test, and iterate on the track using the AWS DeepRacer 3D racing simulator
      • Starting in 2019, compete in the world’s first global autonomous racing league, to race for prizes and a chance to advance to win the coveted AWS DeepRacer Cup

      AWS DeepLens

      AWS DeepLens is the world's first deep learning-enabled video camera for developers. Integrated with Amazon SageMaker and many other AWS services, it allows you to get started with deep learning in less than 10 minutes through sample projects with practical, hands-on examples.

      • Choose your deep learning model from the AWS DeepLens pre-trained model library, or your own models trained with Amazon SageMaker.
      • Deploy your model to the device with a single click.
      • Watch the results in real time in the AWS Management Console.
      AWS DeepLens Video Camera

      ML PROGRAMS | FOR ORGANIZATIONS

      Amazon ML Solutions Lab

      The Amazon ML Solutions Lab combines hands-on educational workshops with advisory professional services to help you ‘work backwards’ from business challenges, and then go step-by-step through the process of developing machine learning-based solutions. You'll be able to take what you have learned through the process and use it elsewhere in your organization to apply machine learning to business opportunities.

      ML PROGRAMS | FOR RESEARCHERS

      Amazon ML Research Grants

      The AWS Machine Learning Research Awards program funds university departments, faculty, PhD students, and post-docs that are conducting novel research in machine learning. Our goal is to accelerate the development of innovative algorithms, publications, and source code across a wide variety of ML applications and focus areas.

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      Machine Learning Training

      Start training on machine learning on AWS with courses based on the same material used to train Amazon's developers through the combination of foundational knowledge and real-world application.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.