2022 Spring Week 4 Train A Model

Homework:

1. Choose one of the workshops below, try to train a model, prepare the dataset, if the model doesn't work well, improve its performance by collecting/cleaning up the data, tweak the model's hyperparameters, and add more layers to the model.

• Training your own gesture classifier: Gestures2Emojis(Guide), ABC Gestures to 3 LEDs(Guide)
  • Try to mix the emoji sketch with the classifier sketch, when a different gesture is detected, type an emoji on the screen.
  • Or add any kinds of output to the Arduino sketch, e.g. light up LEDs.
  • Or train more than 2 gestures
• Training hand pose model
  • Hand pose tracking + KNN Classification, p5 web editor code, demo video
  • Hand pose tracking + Neural Network, demo video
    • Collect data
    • Train the model
    • Run the model
  • After getting the results, add some output based on the results.

2. Document the process of the above exercise with images and a short video.

(Publish 2 on your blog and put your blog link below)

Questions?

• add your question here

Add your name/link to your assignment below

• Your name, [Project name](Project Link), Project Description
• Yves Fogel, [Gesture emoji] (https://wp.nyu.edu/tischschoolofthearts-yvesfogelblog/gesture-emoji/), gesture detection using the 🤦‍♂️ and 🤷‍♂️ emojis
• Lorena https://loloitp.blogspot.com/2022/04/mlxarduino-class-4.html
• Tash Trebisacci: https://www.tatianatrebisacci.com/blog/pcomp-for-machine-learning
• Nati Tsegaye: hand pose: rock, paper, scissor + emojis
• Martha Janicki (M, N and O classifier https://marthajanicki.notion.site/Week-4-Training-a-model-7efccf199c5642f6bdbfe7aa0a2ac6e1)
• Keer Zhao: Gestures to Emojis ❤️ and 🧚‍♀️ classifier
• Sara: Gesture emojis (👊 💪)
• Mohamed: Gestures to Emojis
• Qiongting Zhang: Gestures to emojis(👊💪)
• Stanley: Light hand tracking KNN Classifier with p5 -Minjun Kim p5 sketch https://editor.p5js.org/Mkim1001/sketches/6pIrKzQtU