Once this magic is discovered and acknowledged, it becomes possible to infer from Norse poetry the existence and handling of unconscious archetypes within its associated myths. A few of them have been analyzed in detail and this enabled us to better understand some surprising traits of this mythology... up to detecting 'magical spells' imbedded within Norse poetry (they are usually dubbed as 'Galdralag"). The book ends by sending to the readers a positive of such 'spells' by which "Odinn" self-increased his thoughts and deeds, as given in Havamal.
The book aims at four logically connected targets:
1) spotting Poetic Edda stanzas using a vocabulary calling upon magic for improving our knowledge of ancient Norse magic,
2) checking that no convincing proof of "Christian influences" on Poetic Edda had been provided by the academic community,
3) spotting a few images of Old Norse unconscious archetypes, and
4) finding a few typical instances of the Eddaic meter called Galdralag ("incantation meter").
I am a scientist who spent 45 years of his life as researcher in the French Center for Scientific Research (CNRS) working on the still very new topics of Artificial Intelligence and Machine Learning. This long practice of the scientific approach, instead of ossifying my mind patterns, prompted me towards nonconventional attitudes. Somewhat awkwardly, all this drove me to associate my personal life experiences with a stubborn study of the Old Norse texts containing the original sources of the Northern myths.
Introduction to Machine Learning synthesizes and clarifies
the work of leading researchers, much of which is otherwise available
only in undigested technical reports, journals, and conference proceedings.
Beginning with an overview suitable for undergraduate readers, Kodratoff
establishes a theoretical basis for machine learning and describes
its technical concepts and major application areas. Relevant logic
programming examples are given in Prolog.
Introduction to Machine Learning is an accessible and original
introduction to a significant research area.