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This project provides a comprehensive guide to implementing PCA from scratch and validating it using scikit-learn's implementation. The visualizations help in understanding the data's variance and the effectiveness of dimensionality reduction.
This repository contains all program files and datasets used in implementation of Masters Thesis Research Work for the topic - "Efficient Clustering via Kernel Principal Component Analysis and Optimal One Dimensional Clustering".
Spectral clustering, RBF kernels, and hyperparameter optimization on non-radial data are used to cluster data that gives traditional k-means difficulty.
Python code for Vittorio Bisin's Master's Thesis from the Courant Institute of Mathematical Sciences: 'A Study in Total Variation Denoising and its Validity in a Recently Proposed Denoising Algorithm'
The project aims to research and develop a python package to solve PDEs using the Collocation Method with Radial Basis Functions (RBF). This a project done for the Centro de Investigación en Computación of the Instituto Politénico Nacional under the supervision of Dr. Juan Carlos Chimal Eguía.