International Journal of Algorithms Design and Analysis Review

International Journal of Algorithms Design and Analysis Review Cover

International Journal of Algorithms Design and Analysis Review

ISSN: 2584-1866

Editor Overview

IJADAR maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

Dr. Sharada Patil

Associate Professor Sinhagad Institute of business Administration and Research Editor in Chief International Journal of Algorithms Design and Analysis Review
Email : Institutional Profile Link : http://cms. . .

Publisher

MBA Journals, An imprint of Consortium e-Learning Network Pvt. Ltd.
A-118, 1st Floor, Sector-63, Noida, U.P. India, Pin – 201301

E-mail: [email protected]
(Tel): 0120- 4781 200
(Mob) (+91) 9810078958, +919667725932

About Journal

International Journal of Algorithms Design and Analysis Review (IJADAR): 2584-1866(e) is a peer-reviewed hybrid open-access journal launched in 2023 that focuses on original research and View Full Focus and Scope…

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Journals Particular

Title
International Journal of Algorithms Design and Analysis Review
Journal Abbreviation
IJADAR
Issues Per Year
(Frequency)
2 Issues (Jan-June),(July-Dec)
ISSN
2584-1866
Publisher
MBA Journals, An imprint of Consortium e-Learning Network Pvt. Ltd.
DOI
10.37591/IJADAR
Copyright
MBA Journals, An imprint of Consortium e-Learning Network Pvt. Ltd.
Starting Year
2023
Subject
Computer Science
Language
English
Publication Format
Hybrid Open Access
Type of Publication
Peer-reviewed Journal (Refereed Journal)
Website
https://journals.stmjournals.com/journal/IJADAR
Address
A-118, 1st Floor, Sector-63, Noida, U.P. India, Pin – 201301
Principal Contact
Nikita Mishra [email protected]
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Latest Article
Vol-02 Issue-01 2024
Regular Issue  Subscription Review Article Published on :- May 17, 2024
Study of Machine learning algorithm Santosh Kumar Sen, Neelesh Devre Keywords: Algorithm, Machine Learning, Pseudo Code, Supervised learning, Unsupervised learning, Reinforcement learning

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