An in-depth exploration of clustering algorithms and techniques in machine learning, with applications focus on Object Tracking and Image Segmentation.
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Updated
Sep 14, 2024 - Jupyter Notebook
An in-depth exploration of clustering algorithms and techniques in machine learning, with applications focus on Object Tracking and Image Segmentation.
SDLDpred - Symptom-based Drugs of Lifestyle-related Diseases prediction
A Machine Learning course project within the curriculum of the Data Science specialization at UEH University.
An interactive approach to understanding Machine Learning using scikit-learn
Machine Learning Clustering Techniques for Customer Segmentation - Certification Project
Clustering Visualizer is a Web Application for visualizing popular Machine Learning Clustering Algorithms (K-Means, DBSCAN, Mean Shift, etc.).
Implementations of various supervised and unsupervised machine learning algorithms
Welcome to my Classical Learning Projects repository, where I showcase my work in the fields of supervised and unsupervised learning. Here, you'll find code and datasets for various projects, such as classification and clustering tasks, implemented using popular algorithms like decision trees, neural networks, and k-means.
Visualization and analysis tool to analyze signal strength data to identify areas with poor network coverage
Independent Project - Kaggle Dataset-- I worked with the Mall Customer Segmentation Dataset, which provided a various instances of shoppers of different ages, incomes, etc. I utilized unsupervised ML clustering algorithms to identify useful customer segments.
Python package for multiple change-point detection.
Лабораторные работы по курсу "Технологии программирования на Python"
Implementing the mean-shift algorithm using python for different use cases
This repository contains the Personality Analysis 🧐 of customers of a Grocery store 🏬 with K-means, Agglomerative, Mean shift, DBSCAN clustering. Data preprocessing -> feature engineering -> visuzalization after PCA -> clustering -> profiling.
사용자가 코치의 도움없이 여러 훈련을 개인적으로 할 수 있도록 도와주는 축구 어플리케이션입니다. It is a soccer-practice-application that helps the user to do various training personally without the help of a coach.
Working on five computer vision tasks (optical flow, mean-shift tracking, correlation filter tracking, advanced tracking, and long-term tracking) using the programming language Python.
A lean C++ library for working with point cloud data
Implementation of the Mean Shift Algorithm for image segmentation, used in Bachelor's Thesis at KTH
Sklearn, K-means Clustering, Hierarchical Clustering, DBSCAN, Mean Shift Clustering, Gaussian Mixture Models (GMM), Spectral Clustering, Affinity Propagation, OPTICS (Ordering Points to Identify the Clustering Structure), Birch (Balanced Iterative Reducing and Clustering using Hierarchies), marketing_campaign
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