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Assignment 3 for the DataCamp course X-DataScience Master - scikit-learn API

What we want you to check that you know how to do by doing this assignment:

  • 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.

How?

  • Fork the repository by clicking on the Fork button 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 MYLOGIN using git checkout -b MYLOGIN
  • Make the changes to complete the assignment. You have to modify the files that contain questions in their name. Do not modify the files that start with test_. - Check locally that your solution meet the test by running pytest from the root of the repo. You may need to install pytest using pip or conda.
  • Check the code formating for your solution using flake8. You may need to install flake8 using pip or conda.
  • Open the pull request on GitHub:
    • Create a commit with git add -u and git 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 PR button.
  • Keep pushing to your branch until the continuous integration system is green.
  • When it is green notify the instructors on Slack that your done.

Your mission

  • You should implement a scikit-learn estimator for the KNearestNeighbors class. This corresponds to implementing the methods fit, predict and score of the class in sklearn_questions.py.
  • You should implement a scikit-learn cross-validator for the MonthlySplit class. This corresponds to implementing the methods get_n_splits and split of the class in sklearn_questions.py.

Getting Help

If you need help ask on the Slack of the Datacamp course.