Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.

Dual-domain AI framework for airline RM and digital analytics validation

Data pipeline and inference for Proyecto Respira

Multi-country energy price forecasting system with event awareness and data quality guards.

Powerful XRP price forecasting using public data. Stacking ensemble (Bi-GRU/LSTM/CNN-LSTM + LightGBM/XGBoost, RidgeR). Fuses market OHLCV (CCXT), news sentiment & top50 whale activity. No API keys or signups. Easy setup. CPU/GPU-ready. Multi-horizon single run forecasting. Backtests + Predictions visuals: plot_charts & in-depth tensorboard dash

Theta methods for time series forcasting

Graph-based weather forecasting models. Originally, PyTorch implementation of Ryan Keisler's 2022 "Forecasting Global Weather with Graph Neural Networks" paper (https://arxiv.org/abs/2202.07575)

A comprehensive hospital simulation system integrating discrete event simulation, real-time monitoring, machine learning predictions and interactive dashboards.

An enrollment forecasting application for the Central Connecticut State University School of Business

ml_playground

LLM-Forecast: A Novel Hybrid Forecasting Methodology Integrating ARIMA and Large Language Models

A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.

AI system for energy demand forecasting and grid optimization. Uses time series analysis and weather data to predict energy consumption, optimize renewable energy integration, and prevent grid failures.

Advanced time series forecasting with transformer architectures that can predict complex patterns across multiple horizons with uncertainty quantification.

Lisflood OS (Calibration tool)

An open-source project for traffic data forecasting on the Norwegian road network

Plotly Dashboard for calibrating WOFOST 7.2

Microservice API for price forecasting on BTCUSDT this is a remastered version of the previous version of the project.

A Python-based LSTM model for forecasting XAU/USD (Gold vs USD) prices using historical 15-minute data. This project allows you to train an LSTM neural network, evaluate its predictions, and generate future price forecasts.

Lisflood OS (LISVAP)