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.
It’s time to put machine learning in the hands of every developer. Read this eBook for insights and practical guides designed to accelerate your data and ML journey for your startup.
Read this eBook to discover how your startup can forge ahead, leveraging the full power of ML technologies to optimize your business with new efficiencies and make smarter decisions, faster.
With the industry’s broadest and deepest set of machine learning services, AWS can help your startup to increase performance, reduce costs, and improve customer experiences.
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 »
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.
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.
Amazon SageMaker Studio
SageMaker Studio is the first fully integrated development environment for machine learning to build, train, and deploy ML models at scale.
Amazon SageMaker Autopilot
SageMaker Autopilot is the industry's first automated machine learning capability that gives you complete visibility into your ML models.
Amazon SageMaker Ground Truth
SageMaker Ground Truth makes it easy to build highly accurate training datasets for ML using custom or built-in data labeling workflows for 3D point clouds, video, images, and text.
NEW! Amazon SageMaker JumpStart
SageMaker JumpStart provides a set of solutions for common ML use cases and provides one-click deployable ML models and algorithms from populate model zoos.
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.
Image and 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 »
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 »
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 »
Detect anomalies in metrics
Demand forecasting
Fraud prevention
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.
projects in the cloud happen on AWS
Explore DL Amazon Machine Images (AMI) on AWS »
projects in the cloud happen on AWS
Explore PyTorch on AWS »
projects in the cloud happen on AWS
Explore TensorFlow on AWS »
Machine Learning Startups Building on AWS
