Machine Learning Clustering Techniques for Customer Segmentation - Certification Project

SDLDpred - Symptom-based Drugs of Lifestyle-related Diseases prediction

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

Algorithm implementation in python

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

Project Name: Deep Dive into the Clustering World | ML, Python, Clustering

An investigation into pitch type prediction

Tracking of objects in videos

A web application that use python script for image segmentation Thresholding: Optimal thresholding, Otsu, and spectral thresholding global and local thresholding. Unsupervised segmentation using k-means, segmentation using region growing, agglomerative and mean shift method.