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Check your:
   pip -v list | grep -v "/usr/lib/python3/dist-packages"
    * This will show you any package installed that is not part of Lambda Stack or Ubuntu
      (Ideally these other packages should only be in a virtual environment Python venv or Anaconda/Miniconda

1. Install Miniconda:
   From: https://docs.conda.io/en/latest/miniconda.html#linux-installers
   Current version for Python 3.10:
   
    $ wget https://repo.anaconda.com/miniconda/Miniconda3-py310_22.11.1-1-Linux-x86_64.sh
    $ bash Miniconda3-py310_22.11.1-1-Linux-x86_64.sh
 
2. Activate the environment for miniconda to be active:
   $ . $HOME/.bashrc

   If you want Miniconda installed but not always active, I would not mix Miniconda with python venv,
   since Miniconda blocks the default install.

   I do the following so conda is not always activated, and I can switch between Miniconda and Python venv:
    (base) $ conda deactivate
    $ conda config --set auto_activate_base false

3. Create a environment:
sudo apt install nvidia-driver-525

(You can use 'sudo ubuntu-drivers devices' to figure out what the recommended driver is for you GPU)

conda create --name tf_gpu -c nvidia -c conda-forge tensorflow=2.7 cudatoolkit=11.4 cudnn

     a. Create from the command line:
        $ conda create --name tensorrt_quick tensorflow -c nvidia
     b. Activate the Miniconda environment:
        $ conda activate tensorrt_quick
     c. Install other dependencies:
        $tensorrt_quick) $ pip install pandas scikit-learn matplotlib numpy

 4. Run the code:
   (tensorrt_quick) $ python quick.py

   * I did not need to set LD_LIBRARY_PATH or anything

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