Deep Learning Approach For Time Series Forecasting

This article discusses the recent advancements and challenges in using deep learning methodologies for time series forecasting in various industries. It emphasizes the need for novel designs in deep learning architecture and training algorithms to handle irregular, high-dimensional, and noisy real-world data. The article also encourages researchers to provide publicized datasets for transparency and practical implications in applications.