77axel/Digit-Recognizer
A handwritten digits image classifier built from scratch for learning and experimentation.
This project helps developers and researchers understand how handwritten digit recognition systems work at a fundamental level. It takes images of handwritten digits as input and classifies them, identifying which digit (0-9) each image represents. It's designed for those who want to build and optimize neural networks from scratch without relying on high-level libraries.
Use this if you are a developer or researcher looking to deeply understand the mechanics of Convolutional Neural Networks (CNNs) and low-level performance optimization for image classification.
Not ideal if you need a quick solution for digit recognition and prefer using established deep learning frameworks like TensorFlow or PyTorch, or if you're not comfortable with Python, C, and Fortran.
Stars
15
Forks
2
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jan 13, 2026
Commits (30d)
0
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