--- title: "amazon-sagemaker-examples vs DeepLearningExamples" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/aws-amazon-sagemaker-examples-vs-nvidia-deeplearningexamples" tools: ["aws-amazon-sagemaker-examples", "nvidia-deeplearningexamples"] --- # amazon-sagemaker-examples vs DeepLearningExamples *GraphCanon updated Sep 20, 2026* ## Verdict Pick amazon-sagemaker-examples if jupyter notebooks for illustrating machine learning workflows on Amazon SageMaker; pick DeepLearningExamples if deepLearningExamples offers state-of-the-art deep learning scripts optimized for NVIDIA GPUs, with a focus on reproducibility and performance. It supports a wide range of applications from computer vision to speech and N. [amazon-sagemaker-examples](https://sagemaker-examples.readthedocs.io) reports 11k GitHub stars, 7.0k forks, and 854 open issues, last pushed Sep 9, 2026. [DeepLearningExamples](https://github.com/NVIDIA/DeepLearningExamples) has 15k stars, 3.4k forks, and 321 open issues, last pushed Aug 12, 2024. Figures are from public GitHub metadata via [amazon-sagemaker-examples's repository](https://github.com/aws/amazon-sagemaker-examples) and [DeepLearningExamples's repository](https://github.com/NVIDIA/DeepLearningExamples). | | [amazon-sagemaker-examples](/tools/aws-amazon-sagemaker-examples.md) | [DeepLearningExamples](/tools/nvidia-deeplearningexamples.md) | | --- | --- | --- | | Tagline | Jupyter notebooks for building, training, and deploying ML models using Amazon SageMaker | State-of-the-Art Deep Learning scripts for easy training and deployment with reproducible accuracy and performance on enterprise-grade infrastructure | | Stars | 10,990 | 14,847 | | Forks | 6,955 | 3,406 | | Open issues | 854 | 321 | | Language | Jupyter Notebook | Jupyter Notebook | | Adopt for | Jupyter notebooks for illustrating machine learning workflows on Amazon SageMaker | DeepLearningExamples offers state-of-the-art deep learning scripts optimized for NVIDIA GPUs, with a focus on reproducibility and performance. It supports a wide range of applications from computer vision to speech and N | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0, allowing free use for any purpose with conditions on attribution and license preservation | The license information for DeepLearningExamples is unknown. | | Categories | Inference & Serving, Model Training | Computer Vision, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [amazon-sagemaker-examples](/tools/aws-amazon-sagemaker-examples.md) | [DeepLearningExamples](/tools/nvidia-deeplearningexamples.md) | | --- | --- | --- | | Maintenance | Active (82%) | Dormant (18%) | | Days since push | 10d | 766d | | Open issues (now) | 854 | 321 | | Stars delta | +6 (30d) | +3 (30d) | | Open issues delta | +5 (30d) | 0 (30d) | | Full report | [trust report](/tools/aws-amazon-sagemaker-examples/trust.md) | [trust report](/tools/nvidia-deeplearningexamples/trust.md) | ## Decision facts: amazon-sagemaker-examples - **Adopt for:** Jupyter notebooks for illustrating machine learning workflows on Amazon SageMaker - **License detail:** Apache-2.0, allowing free use for any purpose with conditions on attribution and license preservation ## Decision facts: DeepLearningExamples - **Requirements:** Requires NVIDIA GPUs for optimal performance.; Uses NVIDIA's CUDA-X software stack, including libraries like cuDNN, NCCL, and cuBLAS. - **Adopt for:** DeepLearningExamples offers state-of-the-art deep learning scripts optimized for NVIDIA GPUs, with a focus on reproducibility and performance. It supports a wide range of applications from computer vision to speech and N - **License detail:** The license information for DeepLearningExamples is unknown. ## Choose when ### Choose amazon-sagemaker-examples if… - Tags unique to amazon-sagemaker-examples: aws, data-science, inference, jupyter-notebook. - When you need examples specific to building models with Amazon SageMaker - More recently updated (last pushed Sep 9, 2026). ### Choose DeepLearningExamples if… - Requirements: Requires NVIDIA GPUs for optimal performance.; Uses NVIDIA's CUDA-X software stack, including libraries like cuDNN, NCCL, and cuBLAS.. - Tags unique to DeepLearningExamples: computer-vision, drug-discovery, forecasting, large-language-models. - Also covers Computer Vision. - When you need deep learning scripts optimized for NVIDIA GPUs, including Volta, Turing, and Ampere architectures, for tasks like computer vision, NLP, and speech recognition. ## When NOT to use amazon-sagemaker-examples - For non-AWS environments where cost and integration complexities could outweigh benefits - If seeking open-source tools without ties to a single cloud provider ## When NOT to use DeepLearningExamples - If your infrastructure does not include NVIDIA GPUs, as the scripts are specifically optimized for NVIDIA hardware. - If you are looking for a tool that supports a wider range of hardware or non-NVIDIA GPU environments. - When you need a solution that is not tied to specific frameworks like PyTorch, TensorFlow, or PaddlePaddle, as DeepLearningExamples focuses on these frameworks. ## Common questions ### What is the difference between amazon-sagemaker-examples and DeepLearningExamples? amazon-sagemaker-examples: Jupyter notebooks for building, training, and deploying ML models using Amazon SageMaker. DeepLearningExamples: State-of-the-Art Deep Learning scripts for easy training and deployment with reproducible accuracy and performance on enterprise-grade infrastructure. See the comparison table for live GitHub stats and shared categories. ### When should I choose amazon-sagemaker-examples over DeepLearningExamples? Choose amazon-sagemaker-examples over DeepLearningExamples when Tags unique to amazon-sagemaker-examples: aws, data-science, inference, jupyter-notebook; When you need examples specific to building models with Amazon SageMaker; More recently updated (last pushed Sep 9, 2026). ### When should I choose DeepLearningExamples over amazon-sagemaker-examples? Choose DeepLearningExamples over amazon-sagemaker-examples when Requirements: Requires NVIDIA GPUs for optimal performance.; Uses NVIDIA's CUDA-X software stack, including libraries like cuDNN, NCCL, and cuBLAS.; Tags unique to DeepLearningExamples: computer-vision, drug-discovery, forecasting, large-language-models; Also covers Computer Vision; When you need deep learning scripts optimized for NVIDIA GPUs, including Volta, Turing, and Ampere architectures, for tasks like computer vision, NLP, and speech recognition. ### When should I avoid amazon-sagemaker-examples? For non-AWS environments where cost and integration complexities could outweigh benefits If seeking open-source tools without ties to a single cloud provider ### When should I avoid DeepLearningExamples? If your infrastructure does not include NVIDIA GPUs, as the scripts are specifically optimized for NVIDIA hardware. If you are looking for a tool that supports a wider range of hardware or non-NVIDIA GPU environments. When you need a solution that is not tied to specific frameworks like PyTorch, TensorFlow, or PaddlePaddle, as DeepLearningExamples focuses on these frameworks. ### Is amazon-sagemaker-examples or DeepLearningExamples more popular on GitHub? DeepLearningExamples has more GitHub stars (14,847 vs 10,990). Stars measure visibility, not whether either tool fits your constraints. ### Are amazon-sagemaker-examples and DeepLearningExamples open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to amazon-sagemaker-examples or DeepLearningExamples? GraphCanon lists graph-backed alternatives at [amazon-sagemaker-examples alternatives](/tools/aws-amazon-sagemaker-examples/alternatives) and [DeepLearningExamples alternatives](/tools/nvidia-deeplearningexamples/alternatives) ([amazon-sagemaker-examples markdown twin](/tools/aws-amazon-sagemaker-examples/alternatives.md), [DeepLearningExamples markdown twin](/tools/nvidia-deeplearningexamples/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/aws-amazon-sagemaker-examples-vs-nvidia-deeplearningexamples.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, amazon-sagemaker-examples or DeepLearningExamples? amazon-sagemaker-examples: Active. DeepLearningExamples: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for amazon-sagemaker-examples and DeepLearningExamples? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [amazon-sagemaker-examples trust report](/tools/aws-amazon-sagemaker-examples/trust); [DeepLearningExamples trust report](/tools/nvidia-deeplearningexamples/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=aws-amazon-sagemaker-examples`](/api/graphcanon/graph?tool=aws-amazon-sagemaker-examples) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_