Texts
Neural Networks and Deep Learning, A textbook, Charu C. Aggarwal, 2nd Edition, IBM T. J. Watson Research Center, International Business Machines, Hardcover ISBN 978-3-031-29641-3, Published: June 2023; eBook ISBN 978-3-031-29642-0, Published: 29 June 2023, Publisher Springer Cham
Or 1st edition

Deep Neural Network Applications Published 2022; Hardcover ISBN 978-0-367-21146-2; paperback ISBN 978-1-032-22903-4 eBook ISBN 978-0-429-26568-6; Osipyan, Hasmik; Edwards, Bosede Iyiade; Cheok, Adrian David. Deep Neural Network Applications. CRC Press

Recommended:
Deep Learning, Ian Goodfellow, Yoshua Bengio, and Aaron Courville, Publ. MIT 2016

Course contents and goals
An introduction to neural net concepts, algorithms, and applications. A history of neural nets will be presented along with some discussion of models of biological neural systems. The salient features of neural nets (including architecture, activation functions, weighting scheme) will be characterized. Standard algorithms will be presented, at the basis of traditional neural networks and recent deep learning models. The students will write programs and use neural net software to experiment with standard models and develop an application for a project.

Learning outcomes

• Students will gain fundamental knowledge on neural networks.
• They will learn applications of supervised and unsupervised neural networks.
• They will code and test implementations.
• Application areas include: Image and speech recognition, Predictive analytics, Natural Language Processing (NLP), Autonomous vehicles, Healthcare, Fraud detection, Recommender Systems, Gaming and Simulations (cf.,
  [ https://www.quora.com/What-kind-of-problems-can-neural-networks-solve, T. Amarel. ]
  

Academic integrity policies
You are responsible for making yourself aware of and understanding the policies and procedures in the Undergraduate Catalog that pertain to Academic Integrity. These policies include cheating, fabrication, falsification and forgery, multiple submission, plagiarism, complicity and computer misuse. If there is reason to believe you have been involve in academic dishonesty, you will be referred to the Office of Student Judicial Affairs. You will be given the opportunity to review the charge(s). If you believe you are not responsible, you will have the opportunity for a hearing. You should consult with me if you are uncertain about an issue of academic honesty prior to the submission of an assignment or test.

Additional instructor's notes: Unless permission is given explicitly, the above policy includes cheating by submitting tests, programming assignments or projects where the work (even in part) has been downloaded from the internet; this also applies to text in assignments and project reports. Cooperation among students on submitted work is not allowed. If you are caught there will be consequences.