Sparse Principal Component Analysis via penalised matrix decomposition
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Updated
Apr 12, 2024 - MATLAB
Sparse Principal Component Analysis via penalised matrix decomposition
Details of certified courses covered by me. Includes notes and solutions to programming exercises.
Codes for preforming basic geostatistics
This Repository contains Solutions to Lab Assignments/slides and my personal Notes of the Machine Learning (2022) from Stanford University on Coursera taught by Andrew Ng.
Synthesis of individualized HRTFs based on Neural Networks, Principal Component Analysis and anthropometry
Material from the course of Data Analysis at ENSEM - Université de Lorraine.
Project on hyperspectral-image clustering for the Μ402 - Clustering Algorithms course, NKUA, Fall 2022.
Qualitative and quantitative evaluation of the performance of clustering algorithms in HSI clustering
A MATLAB toolbox for classifier: Version 1.0.7
Functional data analysis of countermovement jump data. It creates linear models from component scores based on a range of data processing techniques, including curve registration.
Face reconstruction and recognition algorithm by principle component analysis (eigenfaces)
This repository contains tools to simulate the ground filtering process of a registered point cloud. The repository contains two filtering methods. The first method uses a normal vector, and fit to plane. The second method utilizes voxel adjacency, and fit to plane.
This repository contains lecture notes and codes for the course "Computational Methods for Data Science"
This repository contains MATLAB Implementation of certain programming assignments of Andrew Ng’s Machine Learning Course on Coursera, created by Stanford University.
Research Goal: Determine if there is hemisphere-dependent change in motor signal origin (measured by EEG) in patients who recover motor function through brain-computer interface (BCI) therapy.
Exploring the Information Content of Glioma Differentiation using SDEs
Task1 - data analysis & classification with multivariate Gaussian classifiers
This repository holds my completed Octave/Matlab code for the exercises in the Stanford Machine Learning course, offered on the Coursera platform.
Anomaly detection on a production line using principal component analysis (PCA) and kernel principal component analysis (KPCA) *from scratch*.
MATLAB implementation of Smooth Manifold FPCA (SM-FPCA)
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