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Applications of Machine Learning models

Session A: Other pre-trained models

Objectives:

  • Understanding how to use pre-trained models other than image classification.
  • Ability to work with PoseNet and ml5.js
  • Ability to work with Object Detection Models (CoCoSSD).
  • Ability to work with Image Segmentation models (UNet and BodyPix) and ml5.js.
  • Week 3 Slides

Models

Data and Model Biographies

Session B

ml5 video tutorials

p5 web editor examples

See demos live

Code

Related Projects

Assignment 3

  1. Read Mixing movement and machine by Maya Man
  2. Read Humans of AI by Philipp Schmitt
  3. Pick one of the models above (PoseNet, HandPose, UNET, BodyPix, CoCoSSD) and following the examples and ml5.js documentation experiment with controlling elements of a p5.js sketch (color, geometry, sound, text) with the output of the model. (You may also choose a ml5.js model not covered here if you like!)
  4. Considering the Model and Data Biography reflect on the the following questions:
    • What questions do you still have about the model and the associated data? Are there elements you would propose including in the biography?
    • How does understanding the provenance of the model and its data inform your creative process?
  5. Document your response to the Data and Model biography as well as your p5.js sketch in a blog post and add a link to the post / your p5 sketch on the Assignment 3 Wiki. In your blog post, include visual documentation such as a recorded screen capture / video / GIFs of your sketch.