This lab will give a quick example-based introduction to basic ideas in machine learning, using Python and scikit-learn.
Slides-ELMED219-2022-MachineLearning
PDF-slides-ELMED219-2022-MachineLearning
Video-ELMED219-2022-MachineLearning
Here's a short extra video that goes through a very similar notebook to the one we use in this lab: https://www.youtube.com/watch?v=OhxUgFNnj1U. You may want to watch this as well.
As Jupyter Notebook is quite new to many of you, you may want to skim through some tutorials. Here are two (also linked under "Getting Started" at MittUiB):
- https://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/index.html
- https://www.datacamp.com/community/tutorials/tutorial-jupyter-notebook
Notebook | 1-Click Notebook |
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ELMED219-Lab0-simple_examples.ipynb constructs predictive models based on some simple data sets. Provides a hands-on introduction to some basic ingredients and techniques in ML. |
Spend some time playing around with the provided examples. You'll find some questions for you to investigate in the notebook. If you're already familiar with machine learning you can try your hand at more advanced examples, or, even better, help out other less experienced team members.