Methods for data segmentation under a sparse regression model

MOSUM procedure for multiple change point estimation

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

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

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

An online internship Data@ANZ Program

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.

Solution to Data@ANZ Virtual Experience Program with Forage.

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

E-commerce exploratory analysis with RFM customer segmentation and metrics