I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
A machine learning approach to Predict the Engineering Stud..:
, In:
2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT)
,
Ahmed, Sheikh Arif
;
Khan, Shahidul Islam
- p. 1-6 , 2019
Link:
https://doi.org/10.1109/ICCCNT45670.2019.8944511
RT T1 <cTitle>2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT)</cTitle>: T1 <Title>A machine learning approach to Predict the Engineering Students at risk of dropout and factors behind: Bangladesh Perspective</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-8944511&Exemplar=1&LAN=DE A1 Ahmed, Sheikh Arif A1 Khan, Shahidul Islam YR 2019 K1 Predictive models K1 Data models K1 Education K1 Feature extraction K1 Machine learning K1 Neural networks K1 Economics K1 neural network K1 dropout detection SP 1 OP 6 LK http://dx.doi.org/https://doi.org/10.1109/ICCCNT45670.2019.8944511 DO https://doi.org/10.1109/ICCCNT45670.2019.8944511 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
