EconPapers    
Economics at your fingertips  
 

Deep Learning

Manish Gupta ()
Additional contact information
Manish Gupta: Microsoft Corporation

Chapter Chapter 17 in Essentials of Business Analytics, 2019, pp 569-595 from Springer

Abstract: Abstract Deep learning has caught a great deal of momentum in the last few years. Research in the field of deep learning is progressing very fast. Deep learning is a rapidly growing area of machine learning. Machine learning (ML) has seen numerous successes, but applying traditional ML algorithms today often means spending a long time hand-engineering the domain-specific input feature representation. This is true for many problems in vision, audio, natural language processing (NLP), robotics, and other areas. To address this, researchers have developed deep learning algorithms that automatically learn a good high-level abstract representation for the input. These algorithms are today enabling many groups to achieve groundbreaking results in vision recognition, speech recognition, language processing, robotics, and other areas.

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:isochp:978-3-319-68837-4_17

Ordering information: This item can be ordered from
http://www.springer.com/9783319688374

DOI: 10.1007/978-3-319-68837-4_17

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-04-01
Handle: RePEc:spr:isochp:978-3-319-68837-4_17