Machine Learning Utils Package

Welcome to this package repo, this package is designed for supporting learning of Introduction to Machine Learning at Imperial College London.

Main Project Structure

.
├── ./ml_utils
├── ./test
├── ./scripts
├── ./requirements.txt
└── ./setup.py

The scripts folder contains the installation scripts of venv in setting up the developing environment. We would discuss the issues about setting up in the following setup part.

The test folder is the placeholder for our private tests of our implementations. The tests use the pytest framework to do unit testing. More information would be covered in the testing part.

Setting up your virtual environment for development

For MacOS users, use the following command to run the script given to create the venv and install dependencies:

./script/install_venv venv

and for Windows users, use an alternative script to do all the jobs above:

./script/install_venv_win venv

The script would not only set up a virtual environment, but also the required python packages for this package, including numpy, pandas, pytest and pytorch etc.

Note: For Linux users and machines, currently I found the installation of pytorch on Linux OS is not working properly, as it would always makes the CI-CD pipeline on shared runner broke. I am trying to solve this quesiton and hope it could be fixed soon.

Testing

Unlike the previous coursework, this time we use the pytest framework to do unit testing. To run all tests, you could run this command:

pytest test/

where pytest as been installed to your virtual environment.

And we could use:

pytest test/test_demo.py

to check the implemntation of a specific part.

To run a specific test, you could specify the testing function name after your testing file, like:

# Just append the reference name to the end of testing file
# do not append parameters after function names
pytest test/test_demo.py::your-testing-function 

That is all of the information you need at the very beginning.