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Machine Learning

Neural Network Visualization
·148 words·1 min
A browser based interactive application that visualizes simple multi-layer perception (MLP) neural networks for the inference of 8x8 pixel images.
BitNetPDK: Neural Networks (MNIST inference) on the "3-cent" Microcontroller
Is it possible to implement reasonably accurate inference of MNIST, the handwritten numbers dataset, on a “3 cent” Microcontroller with only 64 bytes of RAM and 1K of instruction memory?
BitNetMCU: Implementing Neural Networks on the “10-cent” RISC-V MCU without Multiplier
BitNetMCU is a project focused on the training and inference of low-bit quantized neural networks, designed to run efficiently on low-end microcontrollers like the CH32V003. Quantization aware training (QAT) and fine-tuning of model structure allowed surpassing 99% Test accuracy on a 16x16 MNIST dataset in only 2kb of RAM and 16kb of Flash.