Learn how to set up CUDA, CUDNN, Keras, and TensorFlow for GPU-accelerated deep learning on Windows 11 in this comprehensive video tutorial. Follow a step-by-step guide to install the latest version of TensorFlow/Keras with GPU support using pip. Cover essential steps including installing Visual C++, CUDA, CuDNN, and required Python libraries. Explore topics such as NVIDIA video driver installation, Visual C++ setup, CUDA and CuDNN configuration, Anaconda and Miniconda installation, Jupyter setup, environment creation, Jupyter kernel configuration, and TensorFlow/Keras installation. Gain insights into troubleshooting common issues and test your Jupyter setup to ensure everything is working correctly.
Setting Up CUDA, CUDNN, Keras, and TensorFlow on Windows 11 for GPU Deep Learning
Jeff Heaton via YouTube
Overview
Syllabus
Installation Guides
Step 1: NVIDIA Video Driver
Step 2: Visual C++
Step 3: CUDA
Step 4: CuDNN
Step 5: Anaconda and Miniconda
Step 6: Jupyter
Step 7: Environment
Step 8: Jupyter Kernel
Step 9: TensorFlow/Keras
Problems?
Test Jupyter
Taught by
Jeff Heaton
