Files created to the Identificazione dei Sistemi Incerti project. Implemented Kalman Filter, EKF, UKF and a smoother. The Matlab files contain also the white-noise charaterzation of the signal and the outliers identification.

RADseq Data Exploration, Manipulation and Visualization using R

Direct and robust methods for outlier detection in linear regression

The ConfidenceEllipse package provides functions for computing the coordinate points of confidence ellipses and ellipsoids for a given bivariate and trivariate dataset, at user-defined confidence level.

simple but efficient kernel regression and anomaly detection algorithms

Демонстрация применения различных методов очистки данных

[IEEE TKDE 2023] A list of up-to-date papers on streaming tensor decomposition, tensor tracking, dynamic tensor analysis

Toolkit to assist life science researchers in detecting outliers

R-based statistical analysis of Boston Housing Data. Explored feature scales, computed descriptive stats, visualized data, and identified outliers (e.g., higher crime rates in specific areas). Examined variable relationships, calculated correlation coefficients, and presented findings via cross-classifications.

An Apache Spark (Scala) workflow for outlier detection, using K-means clustering.

PalTaqdeer is an AI-Driven Student Success Forecaster. Was developed for Hackathon Google Launchpad, data analysis techniques, Linear regression model, and Flask for the web 🇵🇸

Certifiable Outlier-Robust Geometric Perception

🎯 Database optimization and sales performance analysis for a fine wine company seeking to improve their data management practices and data maturity level - use of Python and JupyterLab (Business insights, Data collection, Cleaning, EDA, and Data Visualization)

Predict laptop prices using machine learning. This project leverages multiple linear regression to achieve an 82% prediction precision. Explore the influence of features like brand, specs, and more on laptop prices.

👨‍💻 Learn how to implement a model of machine learning to solve a real problem

A scalable unsupervised learning of scRNAseq data detects rare cells through integration of structure-preserving embedding, clustering and outlier detection

A Descriptive Data Analysis using Microsoft Excel's advanced data analysis tools.

Pharmaceutical drug performance analysis using matplotlib

Outliers Analysis project done as part of MSc Artificial Intelligence Research