Examples of Tensorflow Lite on Android

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

Sample android application to detect digit drawn using TensorFlow & Firebase model.

This is a machine learning project focused on accurately classifying handwritten digits from the popular MNIST dataset. It provides a collection of code and models that leverage different techniques to achieve high accuracy in recognizing and categorizing digits.

MNIST Digit Recognition Using Scikit-Learn and Ensemble Learning and Then Make an Web-App Using Flask.

A handwritten digit classifier application with python, java, klotin and tensorflow dependencies

This research aims to enhance the performance of LBP-based convolutional neural networks on the automatic recognition of bilingual handwriting.

MATLAB digit classifier based on Andrew NG course

An implementation of multiclass perceptron as a digit recognizer

A simple digit classifier built using the MNIST dataset

This project implements a simple neural network for handwritten digit classification using the MNIST dataset and the Softmax activation function, built with PyTorch. The model is trained to recognize digits (0-9) based on pixel data from 28x28 grayscale images.

Machine learner to classify a single handwritten digit on an image.

This project encompasses a series of modules designed to facilitate the creation, training, and prediction using a PyTorch MLP Neural Network for digit classification based on the MNIST dataset.

Deep Learning project with MNIST dataset to help machines recognizing handwritten digits

Train an neural network to identify digits written on a canvas

In this project, I use Keras and TensorFlow to classify digits and python's Tkinter library to visualize

2nd Project of Course 'Machine Learning' of the SMARTNET programme. Taken at the National and Kapodistrian University of Athens.

Training different models to solve the MNIST digit dataset