Environment_Build.txt

To export the created environment (Anaconda): 
- Activate the environment that needs to be exported in Anaconda.
- Open "CMD.exe" which will open the command prompt window.
- Type: "conda env export > environment.yml" 
- This will export the environment to the current working directory 
- Check the location of the working directory by typing "cd" in the command prompt window 

To recreate the exported environment (Anaconda): 
- Before doing anything, be aware that you can change the environment name inside environment.yml.
- Current environment name is "tensorflow_gpu" and it can be manually changed inside the environment.yml.
- Open Anaconda.
- Open "CMD.exe" which will open the command prompt window.
- Find the location of "environment.yml" and cd into this location.
- Type: "conda env create -f environment.yml".
- This should create the environment with its dependencies.
- To verify the installation, check its contents by typing "conda list" inside the command prompt window.

Alternative Method (longer - follow only if necessary)
- Longer method - if the above method does not work, not using Anaconda, creating a virtual python environment, etc.
- Alternatively, install each major library individually after installing Tensorflow 2.10. 
- The GPU version of Tensorflow 2.10 can be installed with pip install but, find the specific GPU version () to ensure compatibility with Windows.(pip install tensorflow-gpu==2.10.0 from https://pypi.org/project/tensorflow-gpu/2.10.0/)
- You can follow the instructions in "https://www.tensorflow.org/install/source_windows" for a standard build from source.
- This will allow you to install Tensorflow 2.10 with GPU support.
- However, be aware that you need to install other major libraries for the provided script to work without any issues/errors.
- Other major libraries include: Pandas, Matplotlib, Optuna, Numpy, and h5py. If possible use "conda install" vs. "pip install".
- It is recommended to check the required versions of these libraries from the provided "environment.yml" and not installing a random version as it will likely cause issues/errors.
- Warning: Despite following this method, you may still run into issues/errors and may need to fix it with additional research. Therefore, if possible, use the Anaconda method provided above.