A handwritten digits image classifier built from scratch for learning and experimentation.

Simple MNIST Handwritten Digit Classification using Pytorch

It is a Python GUI in which you can draw a digit and the ML Algorithm will recognize what digit it is. We have used Mnist dataset

Binarization Digits of numbers and prepare digits for OCR.

In this part, we developed an interface for Digit Classification using the PyQt5 library in Python.

A "Hello World" ML neural network project features a FastAPI docker image for digit predictions and a React frontend where users can draw digits to see instant predictions

Building a Neural Network for MNIST Digit Classification from Scratch

Kaggle Top 4% Project. CNN Based high precise MNIST like Kannada digit recognizer

TensorFlow2 digits classification - Linear Classifier and MLP

This project uses autoencoders to denoise MNIST images, aiming to improve handwritten digit recognition by refining classifier training data

4th Year Emerging Technologies Project

Workshops

A Django-based web platform that hosts multiple image classification models under one unified interface. Upload an image and get the predicted result instantly.

This project implements a CNN for handwritten digit classification on the MNIST dataset using PyTorch. It uses stacked convolutional layers with dropout, batch normalization, and max pooling to classify 28×28 grayscale digits (0–9) with Softmax output.

A simple project that detects handwritten digits with keras

An overpowered digit classifier built for EE/CNS/CS 148A @ Caltech. Make digits out of anything.

A numpy implementation of the LeNet-CNN 1998 research paper trained on emnist dataset

A Simple MNIST Digit Classifier Neural Network that recognises hand-written numerical digits from the MNIST Digit Recogniser Dataset made from scratch* in Python with 7960 trainable parameters...

Draw Digits to auto recognise them