data-segmentation

Advanced clustering analytics engine for multi-dimensional data segmentation, algorithm benchmarking, and interactive visualization.

MOSUM procedure for multiple change point estimation

Methods for data segmentation under a sparse regression model

Joint smoothing and partitioning of one-dimensional signals and time series with higher order Mumford-Shah models

🍎🔍 Smart AI system that identifies food items in photos and calculates their calorie content automatically. Built with TensorFlow, YOLOv8, CUDA and computer vision for accurate nutrition tracking.

This repository contains a comprehensive collection of SQL scripts based on a learning project aimed at practicing data exploration, analytics, and reporting techniques using SQL.

E-commerce sales project

Colección de scripts de SQL (PostgreSQL) donde se aplican una serie de técnicas de Análisis de Datos: cambios a lo largo del tiempo, análisis acumulativos, análisis de rendimiento, segmentación de datos, análisis de proporciones, etc.

Unsupervised Machine Learning for Customer Market Segmentation with Python

Change-point detection, rate-monitoring and pattern analysis for time-tagged event data using Bayesian Blocks (Scargle, 2013) and Sparse Non-Negative Tucker Decomposition (SNNTD)

this project included data preprocessing, feature selection, and K-means clustering to categorize customers

This Analytics Project contains a collection of SQL scripts that showcase various analytical techniques, including changes over time, cumulative analysis, performance analysis, data segmentation, and part-to-whole analysis.

End-to-end SQL analytics project on Amazon India sales data — pricing strategy, discount behavior, customer segmentation, cumulative analytics, and part-to-whole market share analysis using T-SQL and window functions.

Data Analytics Project: Analyzed Promotions and Provided Tangible Insights to Sales Director

This repository contains a collection of SQL scripts demonstrating various analytical techniques, such as changes over time, cumulative, performance, data segmentation, part-to-whole analysis.

This project is focused on segmenting e-commerce customers using unsupervised machine learning models, specifically clustering algorithms.

End-to-End Enterprise Sales Data Warehouse built with T-SQL (Star Schema). Features advanced analytics including YoY growth trends, cumulative running metrics, customer ranking, and part-to-whole revenue breakdown.

A robust C library for efficient segmentation and reassembly of large JSON objects in IoT and resource-constrained environments. Ensures data integrity and efficiency in network communication.

This repository includes a curated set of SQL scripts that demonstrate a range of analytical techniques, including time-based trend analysis, cumulative metrics, performance evaluation, data segmentation, and part-to-whole analysis.

Customer segmentation using clustering techniques on retail data.