Utilization of Kubeflow for Deploying Machine Learning Models Across Several Cloud Providers-Reference-Cited by-同舟云学术

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Utilization of Kubeflow for Deploying Machine Learning Models Across Several Cloud Providers

Published:2023-12-29 Issue: Volume: Page:1-7
ISSN:
Container-title:2023 3rd International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON)
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Author:

Gill Kanwarpartap Singh¹,Anand Vatsala¹,Chauhan Rahul²,Rawat Ruchira³,Hsiung Pao-Ann⁴

Affiliation:

1. Chitkara University Institute of Engineering and Technology, Chitkara University,Punjab,India

2. Graphic Era Hill University,Computer Science and Engineering,Dehradun,Uttarakhand,India

3. Graphic Era Deemed to be University,Computer Science & Engineering,Dehradun,Uttarakhand,India

4. National Chung Cheng university,Dept. of Computer Science and Information Engineering,Chiayi County,Taiwan R.O.C.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10441789/10441802/10442069.pdf?arnumber=10442069

Reference20 articles.

1. Jet Energy Calibration with Deep Learning as a Kubeflow Pipeline

2. Deployment and Serving ML Models Using Kubeflow and KfServing

3. High-performance neural population dynamics modeling enabled by scalable computational infrastructure

4. CLAIMED‐‐the open source framework for building coarse-grained operators for accelerated discovery in science;Kienzler;arXiv preprint,2023

5. How Can AI be Distributed in the Computing Continuum? Introducing the Neural Pub/Sub Paradigm;Lovén;arXiv preprint,2023

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