Develop like a Pro with NVIDIA + Docker + VS Code + PyTorch

Francesco's blog post from August 3, 2022, guides readers through setting up a development environment for machine learning using NVIDIA GPUs, Docker, VS Code, and PyTorch. It addresses the complexities of installing NVIDIA drivers and emphasizes the convenience of using Docker containers for managing CUDA and cuDNN versions, thereby ensuring code compatibility. The post provides detailed instructions on installing Docker, NVIDIA drivers, and the NVIDIA Container Toolkit, as well as running GPU-accelerated containers with PyTorch. Additionally, it demonstrates how to integrate VS Code for development within containers and discusses deploying machine learning models using Docker, highlighting the benefits of developing directly inside a container to simplify deployment and ensure code reliability.