ML PLATFORM ARCHITECTURE AND CLOUD-BASED MLFRAMEWORK

Authors:

S. Shwetha,Naresh Kumar Sripada,P. Pramod Kumar,V. Hema,

DOI NO:

https://doi.org/10.26782/jmcms.2020.09.00019

Keywords:

Machine Learning,AI,cloud computing,

Abstract

Various heuristic, as well as also meta-heuristic protocols, were related to acquiring the most excellent possibilities. Today period is much attracted alongside the provisioning of self-management, self-learnable, self-healable, as well as likewise self-configurable smart systems. To secure self-manageable Smart Cloud, many Expert systems and additionally Machine Learning (AI-ML) approaches as well as also algorithms are brought back. In this assessment, new style in the treatment of AI-ML approaches, they utilized regions, the main reason, their perks as well as additionally demerits are highlighted. These tactics are more grouped as instance-based machine learning strategies as well as encouragement, learning procedures based upon their ability to learn. This paper provides the details about ML platform architecture and cloud-based MLframework.

Refference:

I. B. Werther – Pre-industrial age of big data, June 2012, http://www.platfora.com/pre-industrial- age-of-big-data/

II. D. Pop, G. Iuhasz – Survey of Machine Learning Tools and Libraries, Institute e-Austria Timi¸soara Technical Report, 2011

III. J Manasa, SN Kumar .”Distinguishing Stress Based on Social Interactions in Social Content Area”.International Journal of Pure and Applied Mathematics, 2018

IV. Komuravelly Sudheer Kumar et al, “A Narrative Improvement Techniques Used with The Expert Systems.” (2019)

V. Kumar, P. Pramod, C. H. Sandeep, and S. Naresh Kumar. “An overview of the factors affecting handovers and effectively highlights of handover techniques for next generation wireless networks.” Indian Journal of Public Health Research & Development, no. 11 (2018): 722-725.

VI. Kumar, S. Naresh, P. Pramod Kumar, C. H. Sandeep, and S. Shwetha. “Opportunities for applying deep learning networks to tumor classification.” Indian Journal of Public Health Research & Development, no. 11 (2018): 742-747.

VII. L. Tierney, A. J. Rossini, Na Li – Snow: A parallel computing framework for the R System, Int J Par- allel Prog (2009) 37:78–90, DOI 10.1007/s10766-008-0077-2

VIII. Pasha, S.N., Ramesh, D., Kodhandaraman, D. &Salauddin, M.D. 2019, “A research to enhance the old manuscript resolution using deep learning mechanism”, International Journal of Innovative Technology and Exploring Engineering, vol. 8, no. 6 Special Issue 4, pp. 1597-1599.
IX. Riaz Muhammad, Samad Baseer, “Authentication and Privacy Challenges for Internet of Things Smart Home Environment”, J. Mech. Cont. & Math. Sci., Vol.-14, No.-1, January-February (2019), pp 258-275

X. Sheshikala, M et al, “Natural Language Processing and Machine Learning Classifier used for Detecting the Author of the Sentence ”. International Journal of Recent Technology and Engineering (IJRTE) (2019).

XI. Sripada, Naresh Kumar et al. “Support Vector Machines to Identify Information towards Fixed-Dimensional Vector Space.” International Journal of Innovative Technology and Exploring Engineering (IJITEE),(2019).

XII. S. Naresh Kumar et al. “A Study on Deep Qlearning and Single Stream Q-Network Architecture”,International Journal of Advanced Science and Technology,2019.

XIII. Sheshikala, M., Kothandaraman, D., Vijaya Prakash, R. & Roopa, G. 2019, “Natural language processing and machine learning classifier used for detecting the author of the sentence”, International Journal of Recent Technology and Engineering, vol. 8, no. 3, pp. 936-939.

XIV. S. R. Upadhyaya – Parallel approaches to ma- chine learning—A comprehensive survey, Journal of Parallel and Distributed Computing, Volume 73, Issue 3, March 2013, Pages 284–292.
XV. Sandeep CH. , S. Naresh Kumar2, P. Pramod Kumar3, “SIGNIFICANT ROLE OF SECURITY IN IOT DEVELOPMENT AND IOT ARCHITECTURE”, J. Mech. Cont. & Math. Sci., Vol.-15, No.-6, June (2020) pp 168-178

XVI. Y. Yu, M. Isard, D. Fetterly, M. Budiu, U. Erlings- son, P. Kumar Gunda, J. Currey – DryadLINQ: A System for General-Purpose Distributed Data- Parallel Computing Using a High-Level Language, In OSDI, 2008

View Download