Simple MNIST Handwritten Digit Classification using Pytorch
-
Updated
Jun 1, 2023 - Jupyter Notebook
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.
Building a Neural Network for MNIST Digit Classification from Scratch
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
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
4th Year Emerging Technologies Project
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.
Draw Digits to auto recognise them
It is about implementing KNN(K nearest neighbor) on Mnist dataset which contains digit images
Code and data for the Digit Recognizer competition on Kaggle.
Add a description, image, and links to the digit-classification topic page so that developers can more easily learn about it.
To associate your repository with the digit-classification topic, visit your repo's landing page and select "manage topics."