BSODsystem32 / MNIST-MLP-Pure-C

What is MNIST-MLP-Pure-C?

This repo delivers a full MLP classifier for the MNIST dataset, trained from scratch in pure C99 with no ML libraries needed. Download MNIST GitHub data via make, train to 98% accuracy using data augmentation and OpenMP, then export a zero-malloc inference model via BN folding for edge devices like ARM Cortex-M. Users get CLI tools for training, benchmarking throughput/latency on test sets, and single-image prediction from PGM or raw files.

Why is it gaining traction?

It stands out as a mnist from scratch GitHub project in C, hitting top mnist mlp accuracy without PyTorch MNIST GitHub or TensorFlow MNIST GitHub dependencies—ideal for avoiding heavy frameworks like mnist mlp Keras. The hook is bare-metal inference ready for MCUs, with benchmarks showing samples/s and ms latency, plus on-the-fly augments like elastic distortion that boost results over basic mnist mlp examples. Devs dig the cross-compile Make targets for real embedded deploys.

Who should use this?

Embedded engineers porting MLPs to microcontrollers, where PyTorch or TensorFlow bloat won't fit. Hobbyists exploring mnist mlp architecture and mnist mlp tutorial in low-level C, or teams needing a lightweight mnist mlp model for sign language MNIST GitHub or Fashion MNIST GitHub baselines. Skip if you're after mnist diffusion model GitHub or visualization tools.

Verdict

Solid learning tool or MCU starter with strong docs and 98% accuracy, but at 10 stars and 1.0% credibility score, it's early-stage—test thoroughly before prod. Grab it for pure-C MLP inference if you're ditching Python deps.

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