Normally, different sets of packages (or different package versions) may be required depending on a project. The safe practice for working with python is to work in different environments. Your project for the next two months is Applied Machine Learning and below are the instructions for creating a virtual environment called appml.
You can either install packages yourself (see the list below) or by running a configuration file we provide.
Installation:
-
Download the file appml.yml (click the link --> click 'Raw' at the top right --> right-click anywhere --> 'Save As' --> save with the correct file name).
-
Navigate to the file location in the terminal and type:
conda env create -f appml.yml -
Activate environment
appml:conda activate appml -
When done, or would like to change the environment, deactivate it:
conda deactivate
To remove the environment (when you no longer need it):
conda remove -n appml --all
You can also use the configuration file for installing with pip package manager (instructions inside): requirements.txt.
(All of these packages are installed by following the instructions above)
- python==3.8.12
- notebook==6.4.6
- numpy==1.21.5
- scipy==1.8.0
- matplotlib==3.5.1
- pandas==1.4.1
- h5py==3.6.0
- scikit-learn==1.0.2
- xgboost==1.5.2
- lightgbm==3.3.2
- seaborn==0.11.2
- tensorflow==2.7.0
- pytorch
- pyg (pytorch-geometric)
- torchvision