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

Quantum MNIST using amplitude encoding instead of dimensionality reduction.

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

An MNIST dataset classifier implemented from scratch in NumPy.

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

MNIST handwritten digit classification using PyTorch

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

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

MNIST Classification with Convolutional Neural Networks

All my machine learning projects and tests.

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

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

Artificial neural networks processed with Tensorflow

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

Naive Implementation of PyTorch framework to solve the MNIST-Digit_Recognition Problem

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