This lab will give a quick example-based introduction to basic ideas in machine learning, using Python and scikit-learn.
❓ 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 | Video* |
|---|---|---|
| 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. |
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Note: The video walk-throughs don't always correspond precisely to the notebooks.
---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. Try out the things you learn in the DataCamp courses by modifying and extending the notebook used in this Lab.