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

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.

A simple project that detects handwritten digits with keras

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...

Enhanced LeNet-5 for MNIST digit classification with minor modifications like dropout for better generalization and OneCycleLR training. High-accuracy baseline for handwritten digit recognition and CNN experiments.

It is about implementing KNN(K nearest neighbor) on Mnist dataset which contains digit images

In this project, I use Keras and TensorFlow to classify digits and python's Tkinter library to visualize

Classification of digits based on their Audio Inputs.

Code and data for the Digit Recognizer competition on Kaggle.