D

data-science

Data Science / Machine Learning Pipeline component for training and deploying ML models using CI

FrontierForge is an AGPL 3.0+ open-source AI-powered research and invention platform designed to transform ideas into reality. By combining scientific research, patent intelligence, semiconductor analysis, architecture design, simulation, knowledge discovery, and autonomous innovation workflows, FrontierForge helps researchers, engineers, inventors, and organizations discover opportunities, generate breakthroughs, validate concepts, and accelerate the development of next-generation technologies. https://roxanneardary.com/frontierforge/

Adaptive Materials Engine (AME) is an open-source engineering intelligence system that helps designers, engineers, and makers replace plastic components with locally sourced, economically viable, and mechanically equivalent or superior materials. When direct substitution is not possible, AME automatically redesigns the system to eliminate plastic dependency while optimizing for cost, performance, and sustainability. https://roxanneardary.com/adaptive-materials-engine/

DeepFiling AI is a nationwide business formation intelligence system that continuously monitors LLC and corporate registrations across all 50 U.S. states. It normalizes filings into a unified dataset, analyzes them in real time, and detects statistical anomalies, surges, and clustering patterns that may indicate emerging industries or unusual economic activity. The system flags deviations from historical norms and generates structured alerts for manual review, turning raw business registration data into actionable economic signals. https://roxanneardary.com/deepfiling-ai/

A practical, linear-algebra-first introduction to data science.

Aston University DG1AID lab repository with AI and data science notes, Python notebooks, NumPy, Pandas, search algorithms and machine learning practice.

About Behavioral finance meets machine learning. Early-warning system to forecast S&P 500 downturns using sentiment, volatility, and unemployment data — with SHAP explainability ,Gradio and Hugging Face deployment.

https://huggingface.co/spaces/Artur-Melnyk/Market-Mood-Forecasting

🚀 Salah Eddine Berredjem - Portfolio A modern, high-performance portfolio website built with Next.js 14 featuring stunning visuals, smooth animations, and optimized performance. Showcasing expertise in Web Frontend Development, AI/ML Engineering, and Data Science.

Fundamental theory and practice in Data Science (DS). 🧮

Analisi della transizione energetica nell'UE27 (2000–2030) con Python, Power BI e Machine Learning. Tre indici sintetici originali (ITE, ICP, RGI) calcolati su dati Our World in Data e proiettati al 2030 tramite regressione lineare.

Progetto IFTS Data Analysis & AI - SIAM1838

Supervised learning pipeline for rare event operational failure prediction, integrating leakage resistant preprocessing, class weighted modeling, precision recall threshold calibration, ROC AUC benchmarking, and permutation based feature importance to analyze production stress drivers.

Projet d’analyse du comportement des utilisateurs Instagram à partir d’un large dataset synthétique (plus d’un million d’utilisateurs).

Le projet explore :

Analyse exploratoire des données (EDA) Prédictions de variables comportementales (stress, âge, clics publicitaires, revenu) Identification de profils utilisateurs avec clustering (KMeans) Interprétation des résultats statistiques en lien avec la vie réelle

Méthodologie : visualisation, corrélations, sélection de modèles, entraînement, évaluation et interprétation.

Technologies : Python, Pandas, NumPy, Matplotlib, Scikit-learn, Jupyter.

Projet réalisé dans le cadre de la formation Développeur en Intelligence Artificielle (Simplon).

API FastAPI permettant d’identifier des espèces de pingouins à partir de données tabulaires optionnelles et/ou d’une image.

L’API renvoie une liste d’espèces probables avec leurs probabilités et inclut :

Classification Machine Learning (RF, KNN, LR) Fusion multimodale (tabulaire + image) Journalisation des requêtes/réponses (SQLite) Interface web pour consulter les logs Interface web pour tester les prédictions Notebooks pour exploration et entraînement

Projet réalisé dans le cadre de la formation Développeur en Intelligence Artificielle (Simplon).

The efficient alternative to Neural Networks. Implements SLRM (Segmented Linear Regression Model) for neural compression and non-linear data modeling, achieving high precision with a fraction of the parameters of a traditional ANN.

Turn any Python project folder into a reproducible job template that creates timestamped, isolated run directories with configurable environments and copy/link behavior.

This repo will have all resources, labs, data which I use/d on Kaggle Network

Tool-driven analytics agent using LLM orchestration, schema-based tools, and a semantic data dictionary.

[2011] Emergency flood forecasting system from Thailand's 2011 crisis. Provided 5-day ARIMA predictions with spatial interpolation across Bangkok, enabling 13 million residents to protect homes when official models failed, shared via public platforms.

[2019-2024] Climate prediction framework using statistical downscaling of GCM data. Combines ARIMA time series, machine learning regression, and stochastic weather generation for 5-day forecasts with spatial interpolation capabilities. The pilot area is the eastern seaboard of Thailand.

Comparação entre Vision Transformers e Métodos Clássicos de Visão Computacional na Segmentação de Exsudatos Lipídicos em Imagens de Retinopatia Diabética. Trabalho de Conclusão de Curso para obtenção de título de bacharel em Engenharia Elétrica na Universidade Federal do Ceará.