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Installation Guides
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Step 1: NVIDIA Video Driver
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Step 2: Visual C++
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Step 3: CUDA
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Step 4: CuDNN
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Step 5: Anaconda and Miniconda
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Step 6: Jupyter
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Step 7: Environment
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Step 8: Jupyter Kernel
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Step 9: TensorFlow/Keras
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Problems?
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Test Jupyter
Description:
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
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