Scientific Journal for Human & Machine Learning

Similar to the first scientific journal, the Scientific Journal of Human and Machine Learning (HML) aims to publish original research and scientific papers of as well as review articles of researchers, academics and students across the globe. The journal mainly covers articles and papers from data science, information technology, machine learning, artificial intelligence, cognitive science, psychology, philosophy, business science, business intelligence/analytics, information management, innovation management, and knowledge management.

The journal aims at meeting the highest expectations of international readers and providing a strong academic channel for active and productive discourse. The originator and one of the associate editors of the journal, Dr. Farshad Badie, states that “HML journal is highly concerned with how modern digital and smart learning approaches can deal with human knowing, learning, teaching, and understanding in various scientific contexts”. Talking further about the aims and objectives of the journal, he also states that “HML journal attempts to deal with the enhancement of the quality of human learning, and teaching, theories based on Artificial Intelligence paradigms and Machine Learning models”. Dr. Badie believes that researchers, scientists, educationalists and philosophers need to make stronger linkages and interconnections between the phenomena of ‘Human Learning’ and ‘Machine Learning’ in our digital age. Accordingly, he believes that one of the most valuable objectives of a broad scope of HML journal is to provide a meeting point for various learning and educational communities.


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