Artificial Neural Networks
by B. Mehlig
Publisher: arXiv.org 2019
Number of pages: 206
Description:
These are lecture notes for my course on Artificial Neural Networks that I have given at Chalmers and Gothenburg University. This course describes the use of neural networks in machine learning: deep learning, recurrent networks, and other supervised and unsupervised machine-learning algorithms.
Download or read it online for free here:
Download link
(6MB, PDF)
Similar books
Artificial Neural Networks: Architectures and Applicationsby Kenji Suzuki (ed.) - InTech
Artificial neural networks may be the single most successful technology in the last two decades. The purpose of this book is to provide recent advances in architectures, methodologies, and applications of artificial neural networks.
(15787 views)
Neural Networksby Rolf Pfeifer, Dana Damian, Rudolf Fuchslin - University of Zurich
Systematic introduction to neural networks, biological foundations; important network classes and learning algorithms; supervised models (perceptrons, adalines, multi-layer perceptrons), support-vector machines, echo-state networks, etc.
(12194 views)
Recurrent Neural Networksby Xiaolin Hu, P. Balasubramaniam - InTech
The concept of neural network originated from neuroscience, and one of its aims is to help us understand the principle of the central nerve system through mathematical modeling. The first part of the book is dedicated to this aim.
(14045 views)
From Complexity to Creativityby Ben Goertzel - Plenum Press
This text applies the concepts of complexity science to provide an explanation of all aspects of human creativity. The book describes the model that integrates ideas from computer science, mathematics, neurobiology, philosophy, and psychology.
(15746 views)