International Journal for Research in Applied Science & Engineering Technology (IJRASET)

ISSN: 2321-9653; IC Value: 45.98; SJ Impact Factor: 7.538

Volume 11 Issue II Feb 2023- Available at www.ijraset.com

V. ACKNOWLEDGEMENTS

Very happy to acknowledge my professor and my guide - Dr .C.M.VINAYA KUMAR sir and finally thank to Co-Scholar friends or my family member who help in research work in this section.

References

[1] DevOps for Data Science: Continuous Delivery and Automation for Data Science Projects by Dipayan Mukherjee and Pratik Mahajan

[2] Machine Learning Operations: Automate ML Workflows with MLOps by Vishnu Rajendran

[3] Mastering MLOps: Leverage DevOps and MLOps to Accelerate Delivery of ML Solutions by Rahul Bhatia and Saptak Sengupta

[4] MLOps: A Hands-on Guide to Building and Operating Machine Learning Platforms and Workflows by Navdeep Gill and Andy Petrella

[5] Practical MLOps: Implementing DevOps for Machine Learning by Abhishek Kumar

[6] DevOps for Data Science: Building Reliable and Scalable Data Pipelines with Python by Chris Fregly

[7] MLOps: Continuous Delivery and Automation for Machine Learning by Aditya Sharma and Abhijit Chaudhari