How to install TensorFlow with GPU support in 2024 | ONLY method that works | Techy Man’s Solutions

TensorFlow is a popular open-source machine learning framework developed by Google. It allows developers to build and train machine learning models efficiently. In 2024, having GPU support for TensorFlow is essential for speeding up the training process of complex models.

Step-by-step guide to install TensorFlow with GPU support:

1. Check GPU compatibility: Before installing TensorFlow with GPU support, make sure your GPU is compatible. You can check the list of supported GPUs on the TensorFlow website.
2. Install CUDA: CUDA is a parallel computing platform and application programming interface model created by Nvidia. You need to install CUDA on your system to enable GPU support in TensorFlow.
3. Install cuDNN: cuDNN (CUDA Deep Neural Network library) is a GPU-accelerated library for deep neural networks. Install cuDNN on your system to further optimize the performance of TensorFlow with GPU support.
4. Install TensorFlow: Finally, you can install TensorFlow with GPU support using pip, the Python package manager. Use the following command to install TensorFlow:

pip install tensorflow-gpu

5. Verify GPU support: Once you have installed TensorFlow with GPU support, you can verify if it is working correctly by running a simple script that utilizes the GPU for computation.

By following these steps, you can successfully install TensorFlow with GPU support in 2024. This method is tried and tested, and it is the only one that works effectively for enabling GPU acceleration in TensorFlow.