In this step-by-step guide you will learn:
How to effortlessly install Ubuntu 24.04 LTS on Windows using WSL 2.
Installing the latest NVIDIA CUDA toolkit compatible with WSL.
Download and configure cuDNN for seamless GPU acceleration in your deep learning projects.
Implementation of a Miniconda environment for streamlined dependency management.
At the end of this video, you will have a powerful development environment, ready to tackle your next AI and machine learning projects!
Keywords: Ubuntu 24.04 LTS, WSL 2, CUDA Toolkit, cuDNN, Deep Learning, Machine Learning, Miniconda, NVIDIA GPU
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sudo apt update
sudo apt upgrade
sudo apt install -y build-essential
CUDA Toolbox:
wget https://developer.download.nvidia.com/compute/cuda/12.4.1/local_installers/cuda_12.4.1_550.54.15_linux.run
sudo sh cuda_12.4.1_550.54.15_linux.run
Path:
nano/.bashrc
export PATH/usr/local/cuda-12.4/bin{PATH::{PATH}}
export LD_LIBRARY_PATH/usr/local/cuda-12.4/lib64{LD_LIBRARY_PATH::{LD_LIBRARY_PATH}}
source /.bashrc
cuDNN
wget https://developer.download.nvidia.com/compute/cudnn/9.2.0/local_installers/cudnn-local-repo-ubuntu2204-9.2.0_1.0-1_amd64.deb
sudo dpkg -i cudnn-local-repo-ubuntu2204-9.2.0_1.0-1_amd64.deb
sudo cp /var/cudnn-local-repo-ubuntu2204-9.2.0/cudnn-*-keyring.gpg /usr/share/keyrings/
sudo apt-get update
sudo apt-get -y install cudnn-cuda-12
Minicond 3.10
wget https://repo.anaconda.com/miniconda/Miniconda3-py310_24.4.0-0-Linux-x86_64.sh
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Video chapters with timestamp:
00:00 Introduction
01:17 WSL – Installing UBUNTU 24.04
03:10 Prepare Ubuntu for CUDA
05:06 Installing the CUDA toolkit
07:06 Configure CUDA toolbox path
08:35 Installing cuDNN
10:43 Miniconda Python 3.10
11:56 a.m. Conclusion
12:35 p.m. Exit
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