An overview of all clustering techniques available in sckit learn library with examples of data.

A generalised soft-clustering algorithm for propagating difficult-to-quantify effects into fuzzy clusters.

A general-purpose algorithm for finding astrophysically-relevant clusters from point-cloud data.

Projeto de people analytics, utilizando machine learning na clusterização de dados de funcionários que poderão deixar a empresa.

Experimental code for simulating mixed-precision k-means

A deep dive into North American grocery e-commerce behaviour based on Instacart's open dataset. [ELT, EDA, ML clustering]

PICAFlow: a complete R workflow dedicated to flow/mass cytometry data, from data pre-processing to deep and comprehensive analysis.

Codes for Practical experiments of Data Warehousing and Mining (Semester V - Computer Engineering - Mumbai University)

Source code of the paper "Min-Max-Jump distance and its applications."

Introduccion a Machine Learning: Sistemas de regresión & clasificación, algoritmos de clusterización, sistemas de recomendación, Machine Learning. Autor: Paulino Esteban Bermúdez R.

LiDAR processing ROS2. Segmentation: "Fast Ground Segmentation for 3D LiDAR Point Cloud Based on Jump-Convolution-Process". Clustering: "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance".

The project utilizes the Online Retail Dataset, a transnational dataset capturing transactions from 01/12/2010 to 09/12/2011 for a UK-based non-store online retail company specializing in unique all-occasion gifts. The dataset includes transactions from both retail and wholesale customers.

A Fuzzy Pre-procressing layer which can be used with embeddings to enrich the information content.

K-Means Image Compression is a Python-based project that compresses an image by reducing the number of colors used. This technique is implemented using the K-Means clustering algorithm, making it ideal for those looking to understand and apply machine learning concepts in image processing.

Implementation of the Leiden algorithm for various quality functions to be used with igraph in Python.

Analysis of bond characteristic in high drug-likeness score compound

Single (i) Cell R package (iCellR) is an interactive R package to work with high-throughput single cell sequencing technologies (i.e scRNA-seq, scVDJ-seq, scATAC-seq, CITE-Seq and Spatial Transcriptomics (ST)).

Repository to store studies of machine learning algorithms implemented in artificial intelligence.

Analisi di dati relativi ai comportamenti di acquisto dei clienti per estrarre informazioni utili e fornire insights dettagliati.

Learn Hub is a web application that helps to learn any technology in a structured & organized way. The idea is to enhance Internet learning by producing search query results based on higher accuracy and relevance of the content, instead of traditional ranking methods.