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Foundations of Machine Learning

Welcome to the course!

These modules will teach you the fundamental building blocks and the theory necessary to be a responsible machine learning practitioner in your own community.  Each module focuses on accessible examples designed to teach you about good practices and the powerful (yet surprisingly simple) algorithms we use to model data. 

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Click on any module to get started learning:
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Code Labs:
All the code labs that accompany these slides can be found here.

This curriculum and code repository was put together by: Sara Hooker, Amanda Su, Brian Spiering, Hannah Song, Melissa Fabros, Kevin Pan, Jack Pfieffer, Rosina Norton, Thuongvu Ho, Mario Carrillo, Parikshit Sharma, Sydney Wong, and Lina Huang. 

Delta Analytics is a 501(c)(3) non-profit. We are entirely volunteer run and all of our educational resources are available for free. We aim to build technical capacity all around the world. Please email inquiry@deltanalytics.org for questions about fair use of these materials and partnering with us.
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© 2022 Delta Analytics, a 501(c)(3) non-profit [Tax ID 47-4911804].
  • About Us
    • Why Choose Delta
    • Leadership Team
    • Our Partners
  • Data Service Grant
    • Data Grants FAQ
    • Past Grant Recipients
  • ML for Good
    • Our Curriculum
    • Teaching Fellows
    • Global Teaching Fellows
  • Apply
    • Fellows >
      • Fellowship FAQ
    • Nonprofits
  • Contact
    • Media & Resources
    • Code of Conduct
  • Blog
  • Donate