Abstract: Amid the accelerating global transition to renewable energy, accurate forecasting has become the cornerstone for unlocking the full potential of solar and wind power in modern power grids, ...

Learn how to predict the maximum distance of a projectile in Python while accounting for air resistance! 🐍⚡ This step-by-step tutorial teaches you how to model real-world projectile motion using ...

Dive into Python Physics Lesson 18 and master numerical integration! In this tutorial, we explain step by step how to use Python to approximate integrals, solve physics problems, and analyze motion ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

“This provides the fundamental building blocks used by everyone in the ecosystem — national meteorological services, financial service firms, energy companies — [to] anyone who wants to build and ...

Abstract: This paper presents a sector-specific employment forecasting framework that integrates deep learning with heterogeneous labor market data, including job postings and macroeconomic indicators ...

GluonTS is a Python toolkit for probabilistic time series modeling, built around Apache MXNet (incubating). GluonTS provides utilities for loading and iterating over time series datasets, state of the ...

Thierry Kalisa started working with new data for real-time economic projections, or “nowcasting,” a decade ago, but the pandemic brought its potential into sharper focus. As a Rwandan finance ministry ...

Google's DeepMind just released WeatherNext 2, a new version of its AI weather prediction model. The company promises that it "delivers more efficient, more accurate and higher-resolution global ...

This project provides a modern, well-structured implementation of hierarchical time series forecasting methods. It supports various forecasting algorithms (ARIMA, Prophet, LSTM) and reconciliation ...