Machine Learning associated with The Machine Learning Partners (MLP), is an international, interdisciplinary journal that deals with the science, policy and practice of Machine Learning defined as the direct and indirect contributions of ecosystems to human wellbeing. 

Machine Learning publishes original, scholarly work in technical domains and the environmental sciences that focuses on innovative education, academic leadership, and advocacy.

Articles may address these topics from different (paradigmatic) perspectives, including basic research, integrated assessment approaches and (ex ante and ex post) policy evaluations. They may be inter-disciplinary or draw from specialized fields within economic, ecological, social and political sciences. Systems addressed may range from natural and semi-natural ecosystems to cultivated systems and urban areas and from local to global scales. However, the research has to be placed adequately, with substance, within the ML framework. Manuscripts dealing with only one aspect of ecosystem services, for example recreation, without putting this single aspect in the broader context of the ML Science, Policy or Practice are not within the scope of this journal.

Scope of the publication includes technical manuscripts in the disciplines of Agriculture, Biological Sciences, Chemistry, Computer and Information Science, Earth Sciences, Ecology, Education, Engineering, Environmental Sciences, Geography Information Science, Geo-physics, Geo-statistics, Humanities, Information Technology, Literature, Business Studies, Management, Material Science, Mathematics, Medical Science, Organizational Studies, Policies & Promotions, Philosophy, Physics, Political Science, Psychological Frameworks, Remote Sensing, Social Science and Zoology.

The Journal is produced two times a year with the express purpose of accelerating the dissemination of scientific knowledge among scientists, technocrats, planners, and elite citizens, as well as promoting the cause of science for a better society.

The Journal strives to promote research of high quality. Current World would like to welcome you to submit articles for consideration and publication in the current and upcoming editions.

You are also required to provide a complete biodata for consideration by the Editorial Board and Advisory Board; selection will be based on seniority and accomplishments.

We also receive opinions and news on the newest products in industries as well as news regarding scholarships, awards, prizes, distinctions, appointments, seminars, and conferences, among others.