Machine Learning is an international forum for research on computational approaches to learning. The journal publishes articles reporting substantive results on a wide range of learning methods applied to a variety of learning problems. The journal features papers that describe research on problems and methods, applications research, and issues of research methodology. Papers making claims about learning problems or methods provide solid support via empirical studies, theoretical analysis, or comparison to psychological phenomena. Applications papers show how to apply learning methods to solve important applications problems. Research methodology papers improve how machine learning research is conducted.
The open access journals are peer reviewed scholarly journals of Journal of Applied Mechanical Engineering. The top open access journals are freely available on the public internet domain, allowing any end users to read, download, copy, distribute, prink, search or link to the full texts of the articles. These provide high quality, meticulously reviewed and rapid publication, to cater the insistent need of scientific community. These journals are indexed with all their citations noted. The top open access journals are indexed in SCOPUS, COPERNICUS, CAS, EBSCO and ISI.
Last date updated on April, 2021