Quantum MNIST using amplitude encoding instead of dimensionality reduction.

An autonomous navigation system for drones in both urban and rural environments.

An MNIST dataset classifier implemented from scratch in NumPy.

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

MNIST handwritten digit classification using PyTorch

This repo hold CV models for the Classification of single digit images. I used Pytorch and the Digit-Recognizer kaggle dataset for the training.

Test project for neural networks - Handwritten digit recognition 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.

A bare-bones (minimal dependencies) implementation of some ML algorithms (classifying/clustering) as part of the Machine Learning postgraduate course assignments in the GUC

OCR for numbers in the MNIST dataset using various ML techniques.

MNIST Classification with Convolutional Neural Networks

Machine Learning model that recognizes hand written digits

All my machine learning projects and tests.

Artificial neural networks processed with Tensorflow

MNIST classifier using CNTK written in C++ and C#. Only used fully connected layers.

This project implements a CNN for handwritten digit classification on the MNIST dataset using PyTorch. It uses stacked convolutional layers with dropout, batch normalization, and max pooling to classify 28×28 grayscale digits (0–9) with Softmax output.

Digit Recognizer - Convolutional Neural Network trained with mnist model using matplotlib - Duke University Class