- Use Git and GitHub
- Work with Python files (and not just notebooks!)
- Do a pull request on a GitHub repository
- Format your code properly using standard Python conventions
- Make your code pass tests run automatically on a continuous integration system (GitHub actions)
- Understand how to code scikit-learn compatible objects.
- Fork the repository by clicking on the
Forkbutton on the upper right corner - Clone the repository of your fork with:
git clone https://github.com/MYLOGIN/datacamp-assignment-sklearn(replace MYLOGIN with your GitHub login) - Create a branch called
MYLOGINusinggit checkout -b MYLOGIN - Make the changes to complete the assignment. You have to modify the files that contain
questionsin their name. Do not modify the files that start withtest_. - Check locally that your solution meet the test by runningpytestfrom the root of the repo. You may need to installpytestusingpiporconda. - Check the code formating for your solution using
flake8. You may need to installflake8usingpiporconda. - Open the pull request on GitHub:
- Create a commit with
git add -uandgit commit -m "UP my solution" - Push your branch on your fork:
git push -u origin MYLOGIN - Go to your repo in your browser and click the
Open a PRbutton.
- Create a commit with
- Keep pushing to your branch until the continuous integration system is green.
- When it is green notify the instructors on Slack that your done.
- You should implement a scikit-learn estimator for the
KNearestNeighborsclass. This corresponds to implementing the methodsfit,predictandscoreof the class insklearn_questions.py. - You should implement a scikit-learn cross-validator for the
MonthlySplitclass. This corresponds to implementing the methodsget_n_splitsandsplitof the class insklearn_questions.py.
If you need help ask on the Slack of the Datacamp course.