Introduction to Machine Learning (I2ML)

This Project offers a free, open source introductory and applied overview of supervised machine learning.

Contents, License, Team and Further Info

Please see the main course site.

Future Development

We are collecting ideas for future development in this list. For suggestions regarding the existing material, please open an issue.

Help is appreciated and welcome!

We hope to continuously improve and expand this course over the coming years. We strongly believe in open source and collaborative work. Please contact us if you think likewise and would like to contribute. See also our contributing guidelines

Are you an ML expert and like the course, but have some feedback or consider extending it? Write an email to Bernd and Fabian (see Team page) or Open an issue.
Are you a student taking the lecture - either at the LMU or online - and you spotted a typo, think we should rephrase something be or even would like to provide a new quiz question or coding example? Please consider providing a pull request. To do so, please check out the devel branch of the repo and add your fixes there. Writing an e-mail or opening an issue with suggested improvements is obviously very welcome as well!
You are none of the above but would like to contribute, get in touch / open issues / create pull requests! We are happy about any help.

Citation

If you use our material, please consider citing us as follows:

@misc{bischl22i2ml,
  author = {Bischl, Bernd and Bothmann, Ludwig and Scheipl, Fabian and Pielok, Tobias and Wimmer, Lisa and Li, Yawei and Kolb, Chris and Schalk, Daniel and Seibold, Heidi and Molnar, Christoph and Richter, Jakob},
  title = {{Introduction to Machine Learning (I2ML)}},
  howpublished = "\url{https://slds-lmu.github.io/i2ml/}",
  year = {2022},
  note = "[Online; accessed yyyy-mm-dd]"
}

This course is based on our concept of open-source educational resources (OSER) as described in our paper:

@InProceedings{bothmann23oser,
  title =    {Developing Open Source Educational Resources for Machine Learning and Data Science},
  author =       {Bothmann, Ludwig and Strickroth, Sven and Casalicchio, Giuseppe and R\"ugamer, David and Lindauer, Marius and Scheipl, Fabian and Bischl, Bernd},
  booktitle =    {Proceedings of the Third Teaching Machine Learning and Artificial Intelligence Workshop},
  pages =    {1--6},
  year =     {2023},
  editor =   {Kinnaird, Katherine M. and Steinbach, Peter and Guhr, Oliver},
  volume =   {207},
  series =   {Proceedings of Machine Learning Research},
  month =    {19--23 Sep},
  publisher =    {PMLR},
  url =      {https://proceedings.mlr.press/v207/bothmann23a.html},
}

License

This work is licensed under a Creative Commons Attribution 4.0 International License.

We would appreciate it if you contact us in case you are re-using our course. Knowing this helps us to keep the project alive. Thank you!

Further topics

We also have a list of unfinished topics that could be again interesting in the future: Link to G-Drive

slds-lmu / lecture_i2ml

readme