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Description: In this step-by-step tutorial, learn how to install and configure Docker Desktop on Windows 11, seamlessly integrate it with WSL Ubuntu 24.04, and unlock GPU acceleration by setting up the NVIDIA Container Toolkit. Watch as I demonstrate how to share your host GPU with Docker containers and test the setup using TensorFlow GPU. To enhance your workflow, I’ll also show you how to connect Visual Studio Code (VS Code) to your Docker container, allowing you to write and run Python code directly inside the container. Whether you're an AI enthusiast, data scientist, or developer, this guide will help you set up a powerful development environment for machine learning and AI projects. Link: https://github.com/mahbub-aumi/Docker... 🔥 What You'll Learn: ✔️ Install Docker Desktop on Windows 11 ✔️ Set up WSL with Ubuntu 24.04 integration ✔️ Install and configure NVIDIA Container Toolkit ✔️ Share GPU resources with Docker containers ✔️ Test GPU acceleration with TensorFlow ✔️ Connect and use VS Code with Docker containers Time Stamp: 0:00 – Introduction 1:00 - WSL Ubuntu 24.04 Installation 5:18 - Installing Docker Desktop on Windows 11 7:17 - Integrate WSL Ubuntu 24.04 with Docker 10:11 - Install and configure Nvidia Container Toolkit 13:19 - Download CUDA Image 16:12 - Make new container from the Image 17:41 - Install TensorFlow with GPU 20:21 - Install and configure VSCode 24:45 - Conclusion 🚀 Boost your AI & ML development workflow with Docker and GPU acceleration! Don’t forget to like, comment, and subscribe for more tech tutorials and Docker guides. 🎯 #Docker #Windows11 #WSL #TensorFlowGPU #NVIDIA #AI #VSCode #MachineLearning #DockerDesktop #GPU