The project encompasses the statistical analysis of data using different clustering and feature selection techniques.
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Updated
Nov 1, 2021 - Python
The project encompasses the statistical analysis of data using different clustering and feature selection techniques.
Analyzing different clustering methods and finding the most suitable one
A UI for Sprocket-VC
Projects using Unsupervised Learning Techniques
Underwater Buoy detection using Gaussian Mixture Models (GMM) and Expectation-Maximization (EM) Algorithm
Image analysis with Gaussian Mixture Model (GMM), with Principal Component Analysis (PCA) for dimensionality reduction of images prior to expectation-maximization (EM) algorithm implementation.
Implementing PCA on MNIST and then performing GMM clustering. PCA is performed from scratch and done for 32, 64, and 128 components. Clustering performed in 10, 7, and 4 clusters.
NUS Pattern Recognition module graded assignments
Machine Learning Project for Course CS7641
This repo is Homework-02 of EE-541(A Computational Introduction to Deep Learning) completed at USC.
Using Python for Data Science
A collection of fundamental Machine Learning Algorithms Implemented from scratch along-with their applications for various ML tasks like clustering, thresholding, data analysis, prediction, regression and image classification.
Clustering Case Study with Gaussian Mixture Models
Implemented the Principal Component Analysis (PCA) & performed dimensionality reduction. Implemented Hierarchical clustering EM algorithm for GMM and performed the clustering operations.
Utilising clustering algorithms like Affinity Propagation, Gaussian Mixture Models, Spectral Clustering, Fuzzy C-means, and Hierarchical Clustering to reveal customer segments and patterns in Uber Eats USA data, generating practical suggestions and visual insights.
This repository contains last project of UT-ML course files(feature extraction, classification, clustering)...
Image Clustering using PCA and GMM: A project implementing Principal Component Analysis and Gaussian Mixture Models for efficient image clustering.
clustering with optimal number of clusters
Machine learning for customer segmentation
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