🔍 Detect fraud in application data using machine learning and data visualization to uncover anomalies and enhance digital integrity.

🛠️ Enable accurate 3D point cloud registration using ROS and Open3D, tested on Nvidia Jetson Orin with Ubuntu 20.04 and Noetic.

🛰️ Automate flood damage mapping and infrastructure assessment using AI-driven models for effective disaster response and recovery operations.

📊 Analyze portfolio risk using PCA on daily returns of 20 large-cap US equities to reveal hidden factors and enhance interpretability.

🛒 Segment mall customers using K-Means clustering to enhance marketing strategies and improve business decisions based on purchasing behavior and demographics.

🐙 Analytical Models in Excel: linear regression, forecasting, classification, and visualizations. Data analytics portfolio of predictive models built in Excel.

Convert RGB images to grayscale and binary formats using Python. Simple, no setup needed. Ideal for image processing tasks. 🖼️✨

this are a different 6 Algorithm with different type of data that is good for practice

🧑🎨 Generate and compare synthetic tabular data using Gaussian Copula and Variational Autoencoders for enhanced analytics and model prototyping.

Daily Machine Learning journey — A consistent log of my progress as I commit every single day to learning and building in the field of ML.

Interface cerveau-machine (EEG) avec Machine Learning. Préprocessing MNE, réduction de dimension (PCA/CSP), pipeline scikit-learn, classification en “temps réel”, validation croisée et évaluation multi-sujets. Projet 42 orienté data science appliquée aux signaux cérébraux.

Efficient similarity search and clustering for Ruby

A RTI library for creating and visualizing Reflectance Transformation Imaging

📚 This book is a comprehensive resource for learning Machine Learning, Deep Learning, and Reinforcement Learning. Our aim is to provide Persian speakers with a guide that enhances their understanding of these advanced algorithms and techniques, facilitating the transition from theory to practical application.

Data Science Projects

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

Machine learning library for classification tasks

This project applies Explainable AI techniques to a Student Dropout dataset, covering pre-, in- and post-modeling explanations, as well as an analysis of their quality. The project was developed for the "Adavnced Topics on Machine Learning" course. 1st Semester of the 1st Year of the Master's Degree in Artificial Intelligence.

A behavioral clustering analysis of cats across observed traits.

A Framework for Detecting DDoS Attacks with Hyper-parameters Optimization, Feature Extraction, Classifiers Combination and Multi-Dataset Testing.