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
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Updated
Sep 14, 2020 - Python
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
Simple MNIST Handwritten Digit Classification using Pytorch
Kaggle Top 4% Project. CNN Based high precise MNIST like Kannada digit recognizer
TensorFlow2 digits classification - Linear Classifier and MLP
In this part, we developed an interface for Digit Classification using the PyQt5 library in Python.
This project uses autoencoders to denoise MNIST images, aiming to improve handwritten digit recognition by refining classifier training data
A simple project that detects handwritten digits with keras
Workshops
I have implemented a Conv2d algo to classify the hand made digits data which can be found on Kaggle . Got an accuracy of 99.76. To download the data for this model go to https://www.kaggle.com/c/digit-recognizer
Classification of digits based on their Audio Inputs.
4th Year Emerging Technologies Project
Code and data for the Digit Recognizer competition on Kaggle.
Digit classification task using Naive Bayes, Perceptron, and MIRA.
In this project, I use Keras and TensorFlow to classify digits and python's Tkinter library to visualize
Making Neural network model from scratch for prediction of digit classification. Its built from scratch using feedforward and backpropagation loops using numpy arrays.
Draw Digits to auto recognise them
It is about implementing KNN(K nearest neighbor) on Mnist dataset which contains digit images
A GUI written in C++ in Ubuntu18. Draw a digit and see the recognition result. Training: k-means extracts patch features + PCA + fc layer + cost + SGD training.
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