MOSUM procedure for multiple change point estimation

Methods for data segmentation under a sparse regression model

A silhouette-guided instance-weighted k-means algorithm that integrates silhouette scores into the clustering process to improve clustering quality.

This project analyzes the Brazilian e-commerce public dataset by Olist, focusing on customer behavior, satisfaction, and value prediction. The dataset contains information about 100,000 orders made between 2016 and 2018 across multiple marketplaces in Brazil, providing comprehensive insights into various aspects of e-commerce operations.

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

E-commerce sales project

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

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)

Unsupervised Machine Learning for Customer Market Segmentation with Python

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

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

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

A manaual Data Augmention for images data also there's an automated approcah by Augmentor libraray

Solution to Data@ANZ Virtual Experience Program with Forage.

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.

E-commerce exploratory analysis with RFM customer segmentation and metrics

Customer segmentation using clustering techniques on retail data.

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