Fundamentals of Machine Learning

Ke-Lin Du () and M. N. S. Swamy
Additional contact information
Ke-Lin Du: Concordia University, Department of Electrical and Computer Engineering
M. N. S. Swamy: Concordia University, Department of Electrical and Computer Engineering

Chapter Chapter 2 in Neural Networks and Statistical Learning, 2019, pp 21-63 from Springer

Abstract: Abstract This chapter deals with the fundamental concepts and theories of machine learning. It first introduces various learning and inference methods, followed by learning and generalization, model selection, and neural networks as universal machines. Some other important topics are also covered.

Date: 2019
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4471-7452-3_2

Ordering information: This item can be ordered from
http://www.springer.com/9781447174523

DOI: 10.1007/978-1-4471-7452-3_2

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().