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

An implementation of multiclass perceptron as a digit recognizer

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

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

A digit-classifier using CNN

An implementation showcasing the deployment of machine learning model onto the flask server with live demo deployed on AWS Lambda.

MATLAB digit classifier based on Andrew NG course

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.

An implementation of a multilayer perceptron in python using numpy. Trained to achieve 96.14% on the MNIST dataset

A digit classifier built using the logistic regression cv learning algorithm.

MNIST Digit Classifier using different models and methods.

Real time digit classifier using python and Deep neural network.

Train an neural network to identify digits written on a canvas