The third edition of this classic book presents a comprehensive treatment of neural networks and learning machines. The book has been revised extensively to provide an up-to-date treatment of the subject.Key Features Include :
On-line learning algorithms rooted in stochastic gradient descent; small-scale and large-scale learning problems.
Kernel methods, including support vector machines and the representer theorem.
Information-theoretic learning models, including copulas, independent components analysis (ICA), coherent ICA, and information bottleneck.
Sequential state-estimation algorithms, including Kalman and particle filters.
Recurrent neural networks trained using sequential-state estimation algorithms.
Insightful computer-oriented experiments.
Stochastic dynamic programming, including approximate and neurodynamic procedures.
ISBN: 9788120340008
Author: Haykin, Simon
Published by: PHI Learning
In addition to resume writing, we provide interview questions and answers according to industry standards. We also give you the opportunity to practice mock interviews and exams. You can get a job learning Online Marketing if you have no prior experience
ReplyDeleteWorking on real-life case studies
digital marketing course in Bangalore