data-science

manufacturing-downtime-analysis

2026-02-26 22:59:37 UTC

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.

Insta Data

2026-02-22 05:37:02 UTC

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).

DS-for-LA

2026-02-18 14:27:01 UTC

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

Next JS Perso Portfolio

2026-02-07 09:44:05 UTC

🚀 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.

Pingouins

2026-02-03 12:30:49 UTC

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).

neural-network

2025-12-11 12:01:29 UTC

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.

insight_agent

2025-12-10 13:48:12 UTC

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

mups

2025-11-13 23:28:22 UTC

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

Emergency Flood Prediction

2025-11-11 20:13:10 UTC

[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.

climate predicton models

2025-11-11 20:09:11 UTC

[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.

Data_Analysis_School

2025-07-11 19:53:21 UTC

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

Trainee_TerraLab_DA_WillianYamauti

2025-06-07 12:53:06 UTC

Este repositório foi criado como parte do programa de Trainee do TerraLab para área de Data Analytics. O objetivo é introduzir os conceitos fundamentais de Análise de Dados por meio de 5 sprints semanais, com foco em Python, Git e visualização de dados.

ml-model-netflix-recommendation-system

2025-05-14 16:03:51 UTC

Project information This is the final source code for my model deployment—a Streamlit application for the Netflix Movie Recommendation System, or we can use the Flask framework. The complete model training, exploratory data analysis (EDA), and data preprocessing are available in my GitHub repository.

GitHub: github.com/aydiegithub/

Live Demo: aydie.in/ml/netflix-recommendation

Contact: business@aydie.in 9036469492 aydie.in

turkiye-car-market-2020

2025-05-05 15:51:57 UTC

A data science project focused on analyzing a car market dataset from Turkey in 2020. The goal is to explore the data, apply various analytical techniques, and derive insights. The specific direction of analysis will be determined through exploration, with potential for building predictive models or visualizing trends in the market.

Kaggle_Playground

2025-05-01 21:06:58 UTC

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

Scalable Machine Learning with SparkML - Census Income Classification

2025-04-19 03:56:57 UTC

Built a complete machine learning pipeline in SparkML using the Adult Census dataset (~48k rows, 14 features). Implemented data preprocessing, feature encoding, cross-validation, and model training with Logistic Regression and Random Forest. Evaluated models with metrics such as AUC and F1-score. Reflected on scalability trade-offs and optimizations in distributed ML.

Lumina

2025-03-21 01:55:00 UTC

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.

web-hypoteste

2024-09-25 11:50:37 UTC

Aplicativo que facilita a realização do teste de hipótese, através de testes T, com uma interface amigável e de fácil utilização.

Data Science ML Component Pipeline

2024-03-25 14:35:43 UTC

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

All in 1 DataScience

2023-09-03 14:27:40 UTC

This repo is a mix of several data science tools. There is a mix of web-scraping of data that is then cleaned, and used to analyze the property market in malta, using prediction models, visualisations and statistical analysis.

There is also visualisations for chess data from the 1980's till 2021. Moreover, there is twitter data, which is then stored in the neo4J nosql dbms.

No data is presented in the git, only the results. Code with the data can be found at: https://drive.google.com/file/d/15EQnRtsngDsFDD_A7g4N1fwCuXI0f_Xi/view?usp=sharing