Android TensorFlow MachineLearning MNIST Example (Building Model with TensorFlow for Android)

A resource-conscious neural network implementation for MCUs

A collection of codes for 'how far can we go with MNIST' challenge

An Intuitive Desktop GUI Application For Recognizing Multiple Handwritten Digits Drawn At The Same Time. Trained On MNIST Dataset and Built With Python, OpenCV and TKinter

Played with Tensorspace a library for Neural network 3D visualization, building interactive and intuitive models in browsers, supports pre-trained deep learning models from TensorFlow, Keras, TensorFlow.js

This repo contains all the necessary files to build a MNIST TinyML application, that works with an OV7670 camera module and TFT LCD module.

Some basic implementations of Variational Autoencoders in pytorch

I implemented a Naive Bayes classifier form scratch and applied it on MNIST dataset.

Problems Identification: This project involves the implementation of efficient and effective KNN classifiers on MNIST data set. The MNIST data comprises of digital images of several digits ranging from 0 to 9. Each image is 28 x 28 pixels. Thus, the data set has 10 levels of classes.

Short python jupyter script, for training Deep learning model for MNIST Dataset about Numbers classification from images and it's evaluation.

Building a model to recognise handwritten numerical digits from images of the MNIST dataset.

Deep learning demos using MNIST data set with multiple neural network models

Deep Neural Networks like Single Layer Perceptron and Multi Layer Perceptron implementation using Tensorflow library on Datasets like MNIST and Naval Mine for categorical Classification. Saving and Restoring Tensorflow "Variables" weights for testing.

VAE Implementation with LSTM Encoder and CNN Decoder

Performs OCR on the MNIST dataset. From my BSc. AI & Robotics at Prifysgol Aberystwyth

Simple NN for MNIST Recognition

A Convolutional neural network heavily based upon the tensorflow advanced MNIST example but equiped with labels to visualize and allowing the user to draw an image and then have the system predict the result.

CNN model for predicting random input.