Browser-based digit OCR demo using canvas input and a Python neural network backend.
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Updated
Jul 12, 2025 - Python
Browser-based digit OCR demo using canvas input and a Python neural network backend.
Trains a simple neural network to recognize binary letter patterns and evaluates its performance under random noise.
This repository implements handwritten digit recognition using a deep neural network trained on the MNIST dataset. It covers data preprocessing, model building, training, and evaluation for high accuracy classification. Additionally, it includes a system for predicting digits from new images. The project demonstrates effective use of deep learning.
This project implements a simple feed-forward neural network for recognizing digits (0-9) from image data using backpropagation. The neural network is trained to identify digits based on pre-processed image data, which is filtered and resized before being used to train the network. The images are in grayscale and are converted to binary values
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