DeepLearningExamples
State-of-the-art deep learning scripts optimized for enterprise hardware.
Optimized deep learning scripts for enterprise-grade infrastructure and GPUs.
This repository provides state-of-the-art deep learning scripts designed for easy training and deployment with reproducible accuracy. It suits AI engineers and researchers working with enterprise-grade NVIDIA hardware.
What it is
It supplies optimized deep learning examples and models across multiple frameworks like PyTorch, TensorFlow2, MXNet, and PaddlePaddle. These examples are tied to the NVIDIA CUDA-X software stack and monthly updated NGC containers.
Who it's for
It suits machine learning practitioners and enterprise developers targeting NVIDIA Volta, Turing, and Ampere GPUs. It does not suit developers looking for CPU-only training or lightweight, framework-agnostic scripts.
Key features
NGC Container Registry
Access monthly updated Docker containers containing optimized deep learning software libraries.
Multi-Framework Support
Utilize scripts built for PyTorch, TensorFlow2, MXNet, and PaddlePaddle frameworks.
Hardware Optimization
Achieve reproducible accuracy and performance on NVIDIA Volta, Turing, and Ampere GPUs.
TensorRT Integration
Run supported models with TensorRT and ONNX for optimized inference deployment.
Up and running in 3 steps
Our honest verdict
What's great
- Includes monthly updated Docker containers via NGC for streamlined deployment
- Pre-configured for automatic mixed precision (AMP) and multi-GPU training
- Supported integration paths for TensorRT and Triton inference server
- Maintains reproducible accuracy and performance benchmarks on NVIDIA hardware
Where it falls short
- Requires specific enterprise-grade NVIDIA GPUs like Volta, Turing, or Ampere
- License is not stated in the repository metadata
- High technical skill required to configure multi-node and containerized environments
Pricing & license
The repository has no stated license or cost in its metadata, and the only cost is running it yourself on compatible enterprise hardware.
Open remote AI-training roles
880 open remote AI-training roles, updated November 15, 2026; most pay $20–$175 an hour. Zekai lists them free; the application goes to the employer’s platform.
Alternatives
Use it, or have us set it up
FAQ
What hardware do I need to run these examples?
You need enterprise-grade NVIDIA GPUs, specifically Volta, Turing, or Ampere architectures.
Are pre-built containers available?
Yes, NVIDIA provides monthly updated Docker containers on the NGC container registry.
