The "Random Swap" algorithm with a random dataset, visuals and example notebooks

Use transfer learning for image classification followed by clustering to create/identify clusters in images

Jupyter Notebook: documentation of the implementation of the ToMATo algorithm to the GUDHI library (Topological Data Analysis), using real datasets.

Notebooks for Global AI Hub ML course in Aug 2022

NBA players clustering and Points prediction

Projeto de machine learning, desenvolvendo um modelo básico de clusterização com um dataset de vinhos

Projeto de Ciência de Dados com o intuito de desenvolver um modelo de clusterização usando machine learning para análises de métricas RFM em uma empresa de e-commerce.

Notebook to enrich clustering going a little bit beyond Sklearn

- Notebook making penguin cluster using KMeans algorithm.

If you liked my analysis, pls upvote my notebook!

Notebook version implementation of unsupervised learning techniques. Analysis and Visualization.

A Jupyter notebook that run PCA and KMeans on population demographic data.

This repository contains notebooks based on kaggle challenge of customers segmentation using ML.

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning

A Jupyter Notebook with a Clustering and PCA Analysis of a Spotify songs dataset.

Machine learning course at IDC. Implemented several amount of ML algorithms in Python using Jupyter notebooks

It contains Google colab notebooks which I have created based on Data analysis and different Machine learning Techniques.

This repository contains the Python code (in a Jupyter Notebook) that was written to build a clustering model that groups cities globally into Metropolitan Statistical Areas (MSAs)

The notebook analyzes Argentina's Atlantic Coast to identify cities with real estate investment potential through data scraping and K-means clustering, revealing three clusters based on internet infrastructure and economic activity.

This project contains a Jupyter Notebook project focused on analyzing customer data. The project involves Exploratory Data Analysis (EDA), data preprocessing, and the implementation of clustering algorithms to derive insights from the data.