--- title: "DeepLearningExamples vs Large-Language-Model-Notebooks-Course" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/nvidia-deeplearningexamples-vs-peremartra-large-language-model-notebooks-course" tools: ["nvidia-deeplearningexamples", "peremartra-large-language-model-notebooks-course"] --- # DeepLearningExamples vs Large-Language-Model-Notebooks-Course *GraphCanon updated Aug 17, 2026* ## Verdict Pick DeepLearningExamples if curated facts for DeepLearningExamples, tailored to its unique features and offerings; pick Large-Language-Model-Notebooks-Course if a developing, comprehensive hands-on course covering a broad array of LLM tools and applications from OpenAI and Hugging Face. [DeepLearningExamples](https://github.com/NVIDIA/DeepLearningExamples) reports 15k GitHub stars, 3.4k forks, and 321 open issues, last pushed Aug 12, 2024. [Large-Language-Model-Notebooks-Course](https://medium.com/@peremartra/list/large-language-models-practical-course-66b4ce5943ce) has 1.8k stars, 447 forks, and 0 open issues, last pushed May 28, 2026. Figures are from public GitHub metadata via [DeepLearningExamples's repository](https://github.com/NVIDIA/DeepLearningExamples) and [Large-Language-Model-Notebooks-Course's repository](https://github.com/peremartra/Large-Language-Model-Notebooks-Course). | | [DeepLearningExamples](/tools/nvidia-deeplearningexamples.md) | [Large-Language-Model-Notebooks-Course](/tools/peremartra-large-language-model-notebooks-course.md) | | --- | --- | --- | | Tagline | State-of-the-Art Deep Learning scripts for various applications | Practical course about Large Language Models | | Stars | 14,844 | 1,821 | | Forks | 3,408 | 447 | | Open issues | 321 | 0 | | Language | Jupyter Notebook | Jupyter Notebook | | Adopt for | Curated facts for DeepLearningExamples, tailored to its unique features and offerings. | A developing, comprehensive hands-on course covering a broad array of LLM tools and applications from OpenAI and Hugging Face. | | Persona | - | - | | Runtime | - | - | | License | - | MIT | | Categories | Inference & Serving, Model Training | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [DeepLearningExamples](/tools/nvidia-deeplearningexamples.md) | [Large-Language-Model-Notebooks-Course](/tools/peremartra-large-language-model-notebooks-course.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Steady (60%) | | Days since push | 734d | 79d | | Open issues (now) | 321 | 0 | | Stars delta | +14 (30d) | +3 (30d) | | Open issues delta | -1 (30d) | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/nvidia-deeplearningexamples/trust.md) | [trust report](/tools/peremartra-large-language-model-notebooks-course/trust.md) | ## Decision facts: DeepLearningExamples - **Adopt for:** Curated facts for DeepLearningExamples, tailored to its unique features and offerings. ## Decision facts: Large-Language-Model-Notebooks-Course - **Adopt for:** A developing, comprehensive hands-on course covering a broad array of LLM tools and applications from OpenAI and Hugging Face. ## Choose when ### Choose DeepLearningExamples if… - Tags unique to DeepLearningExamples: computer-vision, deep-learning, drug-discovery, forecasting. - The NVIDIA GPU Cloud (NGC) Container Registry that integrates with this tool offers the latest updates every month along with rigorous quality assurance. - More GitHub stars (15k vs 1.8k) - visibility, not fit. ### Choose Large-Language-Model-Notebooks-Course if… - Tags unique to Large-Language-Model-Notebooks-Course: chatbots, fine-tuning-llm, huggingface, langchain. - Also covers Evaluation & Observability, LLM Frameworks. - You're seeking an evolving curriculum with projects that apply Large Language Model techniques from various libraries. ## When NOT to use DeepLearningExamples - Avoid using DeepLearningExamples if you do not have access to NVIDIA GPUs, as it is heavily optimized for these specific hardware configurations to provide maximum utilization of Tensor Cores. - If your project requires frameworks that are less common (e.g., MXNet or PaddlePaddle) without the same level of support as PyTorch and TensorFlow on this platform, consider other repositories that n ## When NOT to use Large-Language-Model-Notebooks-Course - Seeking a complete, finalized course where all content is available for immediate use without future updates. - Looking exclusively for theory; the course emphasizes practical application over theoretical depth. ## Common questions ### What is the difference between DeepLearningExamples and Large-Language-Model-Notebooks-Course? DeepLearningExamples: State-of-the-Art Deep Learning scripts for various applications. Large-Language-Model-Notebooks-Course: Practical course about Large Language Models. See the comparison table for live GitHub stats and shared categories. ### When should I choose DeepLearningExamples over Large-Language-Model-Notebooks-Course? Choose DeepLearningExamples over Large-Language-Model-Notebooks-Course when Tags unique to DeepLearningExamples: computer-vision, deep-learning, drug-discovery, forecasting; The NVIDIA GPU Cloud (NGC) Container Registry that integrates with this tool offers the latest updates every month along with rigorous quality assurance; More GitHub stars (15k vs 1.8k) - visibility, not fit. ### When should I choose Large-Language-Model-Notebooks-Course over DeepLearningExamples? Choose Large-Language-Model-Notebooks-Course over DeepLearningExamples when Tags unique to Large-Language-Model-Notebooks-Course: chatbots, fine-tuning-llm, huggingface, langchain; Also covers Evaluation & Observability, LLM Frameworks; You're seeking an evolving curriculum with projects that apply Large Language Model techniques from various libraries. ### When should I avoid DeepLearningExamples? Avoid using DeepLearningExamples if you do not have access to NVIDIA GPUs, as it is heavily optimized for these specific hardware configurations to provide maximum utilization of Tensor Cores. If your project requires frameworks that are less common (e.g., MXNet or PaddlePaddle) without the same level of support as PyTorch and TensorFlow on this platform, consider other repositories that n ### When should I avoid Large-Language-Model-Notebooks-Course? Seeking a complete, finalized course where all content is available for immediate use without future updates. Looking exclusively for theory; the course emphasizes practical application over theoretical depth. ### Is DeepLearningExamples or Large-Language-Model-Notebooks-Course more popular on GitHub? DeepLearningExamples has more GitHub stars (14,844 vs 1,821). Stars measure visibility, not whether either tool fits your constraints. ### Are DeepLearningExamples and Large-Language-Model-Notebooks-Course open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to DeepLearningExamples or Large-Language-Model-Notebooks-Course? GraphCanon lists graph-backed alternatives at [DeepLearningExamples alternatives](/tools/nvidia-deeplearningexamples/alternatives) and [Large-Language-Model-Notebooks-Course alternatives](/tools/peremartra-large-language-model-notebooks-course/alternatives) ([DeepLearningExamples markdown twin](/tools/nvidia-deeplearningexamples/alternatives.md), [Large-Language-Model-Notebooks-Course markdown twin](/tools/peremartra-large-language-model-notebooks-course/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/nvidia-deeplearningexamples-vs-peremartra-large-language-model-notebooks-course.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, DeepLearningExamples or Large-Language-Model-Notebooks-Course? DeepLearningExamples: Dormant. Large-Language-Model-Notebooks-Course: Steady. 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 DeepLearningExamples and Large-Language-Model-Notebooks-Course? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [DeepLearningExamples trust report](/tools/nvidia-deeplearningexamples/trust); [Large-Language-Model-Notebooks-Course trust report](/tools/peremartra-large-language-model-notebooks-course/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=nvidia-deeplearningexamples`](/api/graphcanon/graph?tool=nvidia-deeplearningexamples) - 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/_