Machine Learning for Startups

Implement machine learning (ML) quickly, easily, and at scale with AWS Machine Learning services.

Accelerate your ML journey

We've got your back. We are here to help you find and implement machine learning services that fit your startup needs. Contact us today to speak with an AWS representative to help you get started, answer questions, and accelerate your machine learning journey.

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Featured Guide

Reduce the total cost of ownership with Amazon SageMaker

Download now to learn how leading companies use Amazon SageMaker to improve efficiency, boost productivity, and lower costs.  

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Featured eBook

Automate Document Processing with Amazon Textract

Download now to learn how to extract structured data from documents with speed, flexibility, and accuracy using Amazon Textract.

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FEATURED TUTORIAL

Build, Train, and Deploy a Machine Learning Model in 7 Steps

In this tutorial, follow the seven steps to learn how to use Amazon SageMaker to build, train, and deploy a machine learning model.

Start the tutorial »

Explore the benefits of Machine Learning on AWS

AWS provides ML services for every use case so startups of any size can launch immediately. AWS is among the top rated on Stanford’s 2020 deep learning benchmark, DAWNBench, for the fastest training time, lowest cost, lowest inference latency, and deepest set of security features.
Discover more about ML on AWS »

Free to try

Gain hands-on experience with AWS ML services through AWS free tier. For bootstrapped startups, apply to AWS Activate Founders to access $1,000 USD in AWS Credits.

Low cost

Lower your costs with reliable, scalable services. You only pay for the individual features you need for as long as you use them, without any long-term contracts or complex licensing. 

Powerful performance

Improve team productivity up to 10X using ML collaboration tools and workflows. AWS removes complexity and automates the heavy lifting to manage and monitor ML infrastructure.

Fast to deploy

Deploy ML models with a single click and start generating predictions quickly. ML applications deploy onto auto-scaling instances across multiple availability zones for high redundancy.

Access to AWS experts

Gain access to tools and AWS experts, including Cloud Support Associates and Architectural Guidance. Receive best practices from Trusted Advisors with the AWS Developer Support plan.

Proven

Get inspired by companies around the globe such as Synthetic Gestalt, Coursera, Coinbase, DeepMap, NerdWallet, and Saildrone who launched and continue to grow using ML on AWS. 

Get started with ML on AWS »

Amazon SageMaker

Designed for every type of startup to develop high-quality models that autoscale in production. Amazon SageMaker is a fully managed, modular service that provides the ability to build, train, and deploy machine learning models quickly.

Build

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

Collaborate easily with one-click sharing using Amazon SageMaker Notebooks with all code dependencies automatically captured. Use built-in algorithms and deep learning frameworks optimized for scale, accuracy, and performance. Algorithms run up to 10x faster on Amazon SageMaker.

Choose from hundreds of pre-built models available in AWS Marketplace and use them in Amazon SageMaker.

Train

Train 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 chosen algorithms. 

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

Deploy

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

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

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%.

Read the startup’s guide to building ML on AWS »

AI Services

Startups can use pre-trained AWS AI Services to address common business use cases such as forecasting, image and video analysis, or personalized recommendations. Use these AI Services to easily add intelligence to any application without deep expertise in ML. Startups can integrate these capabilities standalone, or in concert to create sophisticated human-like functionality.

Amazon Personalize

Recommendations

Generate a custom recommendation model based on your data in just a few clicks and start serving personalized content, tailored search results, and targeted marketing promotions with a simple API call.
Amazon Personalize »

Amazon Rekognition

Image & Video Analysis

Integrate face-based user verification into your applications with a simple-to-use API, and enable identity verification for applications like employee badge scanning, banking or credit applications, and security.
Amazon Rekognition »

Amazon Transcribe

Transcription

Automatically convert text to speech. Transcribe customer service calls, to automate closed captioning and subtitling, and to generate metadata for media assets to create a fully searchable archive.
Amazon Transcribe »

Amazon Transcribe

Document Analysis

Instantly extract text and data from virtually any document without manual effort or custom code. Create smart search indexes, build automated approval workflows, and maintain archival rules. 
Amazon Textract »

Explore over a dozen AI services »

ML Frameworks

Choose from TensorFlow, PyTorch, Apache MXNet, and other popular frameworks to experiment with and customize machine learning algorithms. Amazon SageMaker has been key for startups looking to accelerate deep learning projects from concept to production.

81% of deep learning

projects in the cloud happen on AWS
Explore DL Amazon Machine Images (AMI) on AWS »

83% of PyTorch

projects in the cloud happen on AWS
Explore PyTorch on AWS »

85% of TensorFlow

projects in the cloud happen on AWS
Explore TensorFlow on AWS »

Get started with Amazon SageMaker today

Build Highly Accurate Training Datasets at Reduced Costs with Amazon SageMaker Ground Truth (13:58)
Scale up Training of Your ML Models with Distributed Training on Amazon SageMaker (15:18)
Tune Your ML Models to the Highest Accuracy with Amazon SageMaker Automatic Model Tuning (19:52)
Sign up for free ML training from AWS »

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