Guide to Deep Learning Basics : Logical, Historical and Philosophical Perspectives
Publication year: 2020
: 978-3-030-37591-1
This stimulating text/reference presents a philosophical exploration of the conceptual foundations of deep learning, presenting enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cognitive science. The text also highlights select topics from the fascinating history of this exciting field, including the pioneering work of Rudolf Carnap, Warren McCulloch, Walter Pitts, Bulcsú László, and Geoffrey Hinton.
: computer science, Deep Learning, Artificial Intelligence, Ethics of Artificial Intelligence, Connectionism, Essentialism, Philosophical Issues in Artificial Intelligence, Neural Language Models, Word2vec, Overfitting, Soft Computing, Fuzzy Logic, Computational Intelligence, History of Artificial Intelligence
