Hierarchical-Clustering

This project focuses on network anomaly detection due to the exponential growth of network traffic and the rise of various anomalies such as cyber attacks, network failures, and hardware malfunctions. This project implement clustering algorithms from scratch, including K-means, Spectral Clustering, Hierarchical Clustering, and DBSCAN

This project explores and analyzes financial data of a number of securities, applies Hierarchical and K-means clustering to group securities and create cluster profiles to develop personalized portfolios and investment strategies for clients

Binary classification of Brain Tumor

Compilation of various projects based on machine learning algorithms.

A tool to make dendograms from gene expressions.

I performed cluster analysis on a dataset of smart contracts in Python to identify similar risk profiles.

The objective of this project is to categorise the countries using some socio-economic and health factors that determine the overall development of the country and then accordingly suggest the NGO the country which is in dire need of help.

Produire une étude de marché avec Python

Forest Fires Prediction using Unsupervised Learning

Use unsupervised machine learning, PCA algorithm, and K-Means clustering to analyze and classify a database of cryptocurrencies.

Used libraries and functions as follows:

Hierarchical clustering analysis on Credit Card customers dataset.

Explore a comprehensive analysis of Netflix's extensive collection of movies and TV shows, clustering them into distinct categories. This GitHub repository contains all the details, code, and insights into how we've organized and grouped the vast content library into meaningful clusters.

Clustering wedding guests.

This clustering analysis aims to provide valuable insights into the viability of introducing an original language cinema in Milan, Italy.

Mall Customer Segmentation Data

Data prepration and preprocessing for predictive modeling with SAS and Python