Analyze past orders and create innovative features to build a customer's segmentation.

Clustering usuarios de cartão de crédito usando KMeans.

Metis project 5/7

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

Detecting ideal clusters from imdb's movie dataset to segment using unsupervised learning

detect unique colors from an image and express it in 3D

Mining Mastodon for silent users

Data Science - PCA (Principal Component Analysis)

1.Digital Marketing Advertisement Data Segmentation using clustering techniques. 2. Identify Optimum Principal Components that explains the most variance in the Primary Census data.

Customer-Segmentation---Purchasing-Behavior

Face Recognition Algorithm using Unsupervised and Semi-supervised techniques

This repository contains a practical exercise focused on clustering techniques, designed to train and enhance skills in data analysis and machine learning.

A model for predicting customer segmentation using K-Means Clustering and Support Vector Machine Classification

This repo holds a Clustering model written in PySpark.

Agglomerative Clustering from scratch without using built-in library with different hyper-parameters using Python and evaluated the cluster quality using intrinsic and extrinsic scores

This repository contains an implementation for network intrusions clustering. In this task, unsupervised approach is used to cluster network intrusions. It is apart of Assignment2 in Machine Learning course for ROCV master's program at Innopolis University.

Unsupervised Learning model to cluster movies and TV shows on Netflix.

NLP, Recommendation Sys

Implemented an auto-clustering tool with seed and number of clusters finder. Optimizing algorithms: Silhouette, Elbow. Clustering algorithms: k-Means, Bisecting k-Means, Gaussian Mixture. Module includes micro-macro pivoting, and dashboards displaying radius, centroids, and inertia of clusters. Used: Python, Pyspark, Matplotlib, Spark MLlib.

To Identify Major Customer Segments On Transnational Dataset Using Unsupervised ML Clustering Algorithms