Handwritten digits image classification with the MNIST dataset using MultiLayer Perceptron.
-
Updated
Jun 6, 2024 - MATLAB
Handwritten digits image classification with the MNIST dataset using MultiLayer Perceptron.
Code I developed and modified as a part of the Stanford ML course on Coursera.
A classification environment which learns features of fNIRS recordings and can distinguish between children which played alone and children who played with their mothers.
It was developed by creating a hybrid structure with the techniques of K-nearest neighbor algorithm and metaheuristic search algorithms. SOS Algorithm was used as the Meta-Heuristic algorithm.
Multi hidden layers neural network in Octave for classification as generalization from Stanford Class CS229 on Machine learning
This repository contains some machine learning projects as a practise on machine learning course on Coursera for Prof. Andrew Ng from Stanford University.
Add a description, image, and links to the classification-model topic page so that developers can more easily learn about it.
To associate your repository with the classification-model topic, visit your repo's landing page and select "manage topics."