Handwriting Classification Implemented in Assembly

Handwriting Classification Implemented in Assembly

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Implemented a classification algorithm in assembly language to read pictures of handwritten numbers
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Implemented a neural network in RISC-V assembly language to read pictures of handwritten numbers. Used the MNIST database, a sample set of labeled, normalized images of handwritten digits to train and test the machine learning algorithm. My final implementation was performant and memory safe. This project was part of CS61C, a Computer Architecture / Machine Structures course I took at Berkeley.