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
TensorFlow2 digits classification - Linear Classifier and MLP
Making Neural network model from scratch for prediction of digit classification. Its built from scratch using feedforward and backpropagation loops using numpy arrays.
Implement digit classification using LibSVM libarary.
Simple MNIST Handwritten Digit Classification using Pytorch
Designd a ML Model from the MNIST dataset to identify digit classification using the SVM algorithm.
This project uses autoencoders to denoise MNIST images, aiming to improve handwritten digit recognition by refining classifier training data
Classification of digits based on their Audio Inputs.
Code and data for the Digit Recognizer competition on Kaggle.
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
Digit classification task using Naive Bayes, Perceptron, and MIRA.
identify digits from MNIST dataset of tens of thousands of handwritten images
The MNIST dataset was used to train a neural network having a single linear layer with SoftMax employed in the criterion function (Cross Entropy Loss) to classify handwritten digits in classes 0 to 9. The model yielded a 92% accuracy on the MNIST test dataset in 10 training epochs.
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.
In this project, I use Keras and TensorFlow to classify digits and python's Tkinter library to visualize
In this part, we developed an interface for Digit Classification using the PyQt5 library in Python.
Draw Digits to auto recognise them
It is about implementing KNN(K nearest neighbor) on Mnist dataset which contains digit images
Welcome to the Digit Classification Project! This project focuses on training a model to classify handwritten digits and using the trained model to predict digits from new images.
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