Analysis and Implementation of Microsoft Azure Machine Learning Studio Services with Respect to Machine Learning Algorithms-Reference-Cited by-同舟云学术

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Analysis and Implementation of Microsoft Azure Machine Learning Studio Services with Respect to Machine Learning Algorithms

Published:2023 Issue: Volume: Page:91-106
ISSN:1876-1100
Container-title:Modern Electronics Devices and Communication Systems
language:
Short-container-title:

Author:

Singh Soni,Ramkumar K. R.,Kukkar Ashima

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-6383-4_7

Reference26 articles.

1. https://www.dgp.toronto.edu/~hertzman/411notes.pdf.

2. Das TK (2015) A customer classification prediction model based on machine learning techniques. In: International conference on applied and theoretical computing and communication technology (iCATccT), pp 321–326. IEEE

3. Salmi N, Rustam Z (2019) Naïve Bayes classifier models for predicting the colon cancer. IOP Conf Ser Mater Sci Eng 546:52–68

4. Osisanwo FY, Akinsola JET, Awodele O, Hinmikaiye JO, Olakanmi O, Akinjobi J (2017) Supervised machine learning algorithms: classification and comparison. Int J Comput Trends Technol (IJCTT) 48:128–138

5. Soh J, Singh P (2020) Introduction to Azure machine learning. In: Data science solutions on Azure. Apress, Berkeley, CA

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