How can I light the leds with tensorflow lite?

Hi I have accelometer data like below. I want to light the user leds that on stm32f407 discovery board.

My goal is when estimated_x hit the 200 or above I want to light led_13 or when estimated_z hit the 200 or above I want to light led_12. I am aware that I can make it without using ml but it is not my goal. I want to teach it to the ml. How can I achive this ? Should I use lineaar regression ? If so can you provide me some usefull links i am a beginner.

D: estimated_x estimated_y estimated_z
D: time(ms) (0x20000168,6) (0x20000164,6) (0x20000170,6)
D: 0.13 208.644287 134.083832 161.288589
D: 0.72 208.644287 134.083832 161.288589
D: 1.23 208.644287 134.083832 161.288589
D: 1.72 208.644287 134.083832 161.288589
D: 2.23 208.644287 134.083832 161.288589
D: 2.73 208.644287 134.083832

Hi @Fahri_Kaan_Uslu,

Let’s start with the basic Machine Learning Models, such as:

  1. Logistic regression
  2. Support Vector Machines (SVM)
  3. Decision Trees
  4. Random Forests
  5. Gradient Boosting
  6. Neural Networks

Once you go through above simple machine learning models, then try to look at this TensorFlow guide for advanced model like Neural Networks.

You may want to start with simpler models like logistic regression or decision trees and gradually explore more advanced models if needed. It’s also a good idea to experiment with different models and compare their performance to find the best fit for your specific task.

If you can go through medium articles

I hope this helps!