AWS Deep Learning AMIs Alternatives (January 2026)

AWS Deep Learning AMIs provides ML practitioners with curated, secure frameworks, dependencies, and tools to accelerate and scale deep learning in the cloud.

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1.
Docker Images for Machine Learning - AWS Deep Learning Containers - AWS
https://aws.amazo
.com/machine-learning/containers/

AWS Deep Learning Containers are Docker images preinstalled with deep learning frameworks that make it easy to deploy custom machine learning environments.

3.
Machine Learning Service - Amazon SageMaker - AWS
https://aws.amazo
.com/sagemaker/

Build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows.

4.
Deep Learning Containers  |  Google Cloud
https://cloud.googl
.com/deep-learning-containers/

Prepackaged and optimized deep learning containers for developing, testing, and deploying AI applications on TensorFlow, PyTorch, and scikit learn.

5.
Amazon EC2 - Cloud Compute Capacity - AWS
https://aws.amazo
.com/ec2/

Amazon EC2 provides secure, resizable compute in the cloud, offering the broadest choice of processor, storage, networking, OS, and purchase model.

7.
Efficient Batch Computing – AWS Batch - AWS
https://aws.amazo
.com/batch/

AWS Batch allows developers, scientists, and engineers to efficiently process hundreds of thousands of batch and machine learning computing jobs on AWS.

8.
Recommender System, Recommendation Engine - Amazon Personalize - AWS
https://aws.amazo
.com/personalize/

Amazon Personalize is an ML service that helps developers quickly build and deploy a custom recommendation engine with real-time personalization and user segmentation.

9.
Machine Learning Devops - Amazon DevOps Guru - AWS
https://aws.amazo
.com/devops-guru/

Amazon DevOps Guru is a machine learning service designed to detect abnormal operating patterns so you can identify issues before they impact your customers.