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

An implementation of multiclass perceptron as a digit recognizer

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.

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

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.

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

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

A simple digit classifier built using 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.

A Machine Learning project that uses EM and Bernoulli mixes to classify digits

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

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

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.