Deep Learning in a Nutshell: History and Training

This series of blog posts aims to provide an intuitive and gentle introduction to deep learning that does not rely heavily on math or theoretical constructs. The first part in this series provided an overview over the field of deep learning, covering fundamental and core concepts. In this second part, we look briefly into the history of deep learning and then proceed to methods of training deep learning architectures quickly and efficiently. The third part focuses on learning algorithms, unsupervised and sequence learning. I wrote this series in a glossary style so it can also be used as a reference for deep learning concepts. History A Short History of Deep Learning The earliest deep-learning-like algorithms that had multiple layers of non-linear features can be traced back to Ivakhnenko and Lapa…

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