My projects from the Stanford Machine Learning course offered on Coursera by Professor Andrew Ng.

A New Support Vector Finder Method, Based on Triangular Calculations and K-means Clustering

Project on funding-allocation for the Μ402 - Clustering Algorithms course, NKUA, Fall 2022.

K-Means (Lloyd's Methos) using MATLAB

A jigsaw puzzle solver term project.

Implement different Machine learning algorithms

Code for the exercises of the Machine Learning course offered by Stanford University on Coursera.

matlab toolbox for ml

Sparse simplex projection-based Wasserstein k-means

Course Lab work for Image analysis and computer vision

An Exact Solver for Cardinality-constrained Minimum Sum-of-Squares Clustering

machine-learning octave neural-networks linear-regression logistic-regression multi-class-classification support-vector-machines k-means-clustering principal-component-analysis anomaly-detection recommender-systems

AUST_CSE 4.2 Pattern Recognition Lab Codes and Experiments

A set of ML algorithms implemented in MATLAB

Matlab scripts for analyzing calcium imaging data presented in "Neural Coding of Leg Proprioception in Drosophila" (Mamiya, Gurung, and Tuthill (2018) Neuron: DOI:https://doi.org/10.1016/j.neuron.2018.09.009)

A Matlab script that applies the basic sequential clustering to evaluate the number of user groups by using the hierarchical clustering and k-means algorithms. Using the k-means fold the classifiers that are a neural network and the other least squares to evaluate them.

Machine Learning and Analysis of Big Data course, Computer Science M.Sc., Ben Gurion University of the Negev, 2020

Machine Learning principles in Octave/Matlab from Andrew Ng Specialization

Code written for MATH 444 projects Spring 2021

detecting fake news using linguistic features. ML techniques ranging from hard and soft-clustering to fuzzy inference systems and neural networks. included FMID5 - Fuzzy Model Identification toolbox in MATLAB