S

scikit-learn

Materials on various sections in Computer Science (CS). 🎓

Self-hosted forecasting + prediction service. Five zero-shot time-series foundation models (Chronos-2, TimesFM 2.5, Moirai-2, Toto-1, Sundial) across six forecast types, plus nine supervised tabular ML backends (LightGBM, XGBoost, sklearn family) with calibrated / stacking / diversified meta-learners. Unified REST API + MCP server.

Open industrial IoT platform for predictive maintenance: four sensor nodes, a FastAPI backend, Isolation Forest anomaly detection and a live Next.js dashboard. Reveal before failure.

Reproducible Python experiments turning treatment-effect estimates into targeting policies, with cross-fitted policy evaluation, uncertainty analysis, and policy trees on Hillstrom's randomised email experiment.

Analysis of Kilter Board data, along with predictive models for V-grades based on holds and angle.

Analysis of Tension Board 2 data, along with predictive models for V-grades based on holds and angle.

Practical tasks on Deep Learning (DL) and Neural Networks (NN). 🤖

A production-grade machine learning system for classifying celestial objects — stars, galaxies, and quasars — from 500,000 photometric observations sourced from the Sloan Digital Sky Survey (SDSS DR18). The pipeline covers LOF-based outlier detection, SMOTEENN class balancing, and SelectKBest feature selection, with six classifier configurations benchmarked against each other. Random Forest achieved the highest accuracy at ~99.51%, while LightGBM was selected for deployment due to its faster inference, smaller footprint, and clean ONNX export path. The system is fully containerized with Docker, backed by a CI/CD pipeline, and served live via a Gradio interface on Hugging Face Spaces.

A data mining project analyzing hate crime patterns in the United States from 2017 to 2025, using clustering, predictive modeling, and association rule mining.

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

A set of data machine learning/deep learning projects exploring various datasets — a place to test ideas, models, and modern stacks.

AI-Powered Network Packet Analyzer with ML Anomaly Detection - Scapy/scikit-learn, detects port scans, DNS tunneling, DDoS, C2 beaconing, data exfiltration. For authorized security monitoring only.

https://ayinedjimi-consultants.fr

Intelligent Log Parsing and Anomaly Detection with Machine Learning

https://ayinedjimi-consultants.fr

Simple ML Project using regression models and KMeans clustering to predict Y from A and B, classify results, and expose predictions through a FastAPI API.

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

Introduction to classification using machine learning and deep learning (PyTorch, TensorFlow, Keras)

Statistics for sci-kit learn.