Novel Advances in the Development of Machine Learning Solutions for Scientific Programming

Scientific programming is a multidisciplinary field that uses advanced methods to understand and solve complex problems. Meanwhile, machine learning is the field that uses statistical techniques to give computer systems the ability to learn and extract knowledge from data, answering questions, and solving problems in various application domains, without the need of being explicitly programmed. Both are exciting, complex, and interrelated fields in which advances are taking place at a great pace. This special issue aims to bring together some of the most important advances related to the unio‎n of scientific programming and progresses in the field of machine learning. Thus, after a rigorous selection process, this number includes 9 works that allow us to continue exploring the possibilities that machine learning can provide, particularly for scientific programming.