Objective: To compare the application of the ARIMA model, the Long Short-Term Memory (LSTM) model and the ARIMA-LSTM model in forecasting foodborne disease incidence. Methods: Monthly case data of ...

ABSTRACT: Despite its significant impacts on climate, environment, and public health, air pollution monitoring in Africa is still sparse. This study developed a machine learning framework of four ...

The implementation of a business model involves a detailed understanding of the process through which a company creates, delivers, and captures value. The operational challenges here include the ...

├── data/ # Raw and processed data ├── notebooks/ # Jupyter notebooks for analysis │ ├── 01-eda.ipynb # Exploratory Data Analysis │ ├── 02-preprocessing.ipynb # Data cleaning & feature engineering │ ...

Time series forecasting is a critical tool in financial markets for predicting stock prices, enabling informed decision-making. The provided Jupyter notebook demonstrates an ARIMA model for ...

Abstract: Robust wind power forecasting in the presence of missing data remains a critical challenge for efficient grid management and energy trading. This paper proposes a novel methodology that ...

Written by Ken Huang, CSA Fellow, Co-Chair of CSA AI Safety Working Groups and Dr. Ying-Jung Chen, Georgia Institute of Technology. This implementation guide provides a comprehensive, hands-on ...

The well-funded and innovative French AI startup Mistral AI is introducing a new service for enterprise customers and independent software developers alike. Mistral's Agents application programming ...

Meta AI has released Llama Prompt Ops, a Python package designed to streamline the process of adapting prompts for Llama models. This open-source tool is built to help developers and researchers ...

Monocular depth estimation involves predicting scene depth from a single RGB image—a fundamental task in computer vision with wide-ranging applications, including augmented reality, robotics, and 3D ...