MNIST testing scripts for Tensorflow for the paper about Automatic Differentiation in Simulink

A simple python implementation of a Neural Network from scratch

MNIST- Machine Learning with tensorflow

Hand Written Web Application for Digit Recognition Using Tensorflow and Python

Deep Neural Network implementation for recognizing digit using MNIST data set and Tensorflow

Programmes presenting issues related to artificial intelligence and machine learning.

My implementation of the Random Forest algorithm, using ID3 decision trees

Get and solve the handwriting dataset from MNIST

PCA vs Autoencoder

This is a simple Django REST framework application for a prediction endpoint on the MNIST trained CapsNet model

Digit Recognizer is a CNN based model which recognizes images of handwritten digits using keras.

Pytorch Implementation of a simple GAN for MNIST [inspired by DCGAN]

Handwritten Digit Recognizer written in python using tkinter(for gui), keras(models, datasets etc.), PIL(Image grabbing & filtering) and Tensorflow modules.

Handwritten digit recognition system trained on MNIST data.

This module is limited to making use of the classifier KNeighborsClassifier from sklearn to apply it to the recognition of handwritten digits in the MNIST file, with a hit rate about 98,65% in test and extraordinary simplicity, especially compared to the complexity of classifiers based on neural networks. It also shows full sensitivity.

In this project I explore four diffrent approaches to generate MNIST image with general adversial network.

A simple auto encoder

Implement transfer learning on the MNIST dataset in Keras framework, as well as self-designed datasets division code.