PARSA-MHMDI/TinyML
Embedded AI - Power Consumption Prediction uses TinyML to forecast energy usage on an STM32F407G board. It trains a TensorFlow model, converts it to TFLite, and runs predictions on embedded hardware for real-time analysis. 🚀
No commits in the last 6 months.
Stars
2
Forks
—
Language
C
License
MIT
Category
Last pushed
Feb 03, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/PARSA-MHMDI/TinyML"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
pytorch/executorch
On-device AI across mobile, embedded and edge for PyTorch
catalyst-team/catalyst
Accelerated deep learning R&D
mit-han-lab/mcunet
[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2:...
z-mahmud22/Dlib_Windows_Python3.x
Dlib compiled binaries (.whl) for Python 3.7-3.14 and Windows x64
gigwegbe/tinyml-papers-and-projects
This is a list of interesting papers and projects about TinyML.