DSIPTS: A high productivity environment for time series forecasting models

Today's article comes from Elsevier's SoftwareX journal. The authors are Gobbi et al., from FBK (Fondazione Bruno Kessler) University, in Italy. In this paper they debut a new tool, written in Python, that allows you to train and compare deep-learning models with far less effort than ever before. We're going to break down the paper, but also explore the Github repository the authors provided. Let's get started.

DOI: 10.1016/j.softx.2024.101875