A Research based on Predicting Software Project Outcomes and Skill Gaps using Machine Learning

Authors

  • Ms. Renu ,Dr. Rajat Kumar

Keywords:

Software Engineering, Intelligent Recommender System, ML in Software Management, Project Risk Prediction

Abstract

The data processing sector's growth has led to increased reliance on data-driven businesschoices and enterprise-scale data models. However, the accuracy of these choices depends onthe quality of the data used in analysis. This paper proposes a novel framework for data

References

B. Wang and W. Zhang, "Research on Edge Network Topology Optimization Based on

Machine Learning," 2023 5th International Conference on Applied Machine Learning

(ICAML), Dalian, China, 2023, pp. 41-46, doi: 10.1109/ICAML60083.2023.00018.

Bolognani S, Bof N, Michelotti D, Identification of power distributionnetwork topology via

voltage correlation analysis [A]. // IEEE Conference on Decisionand Control[C], Piscataway

: IEEE, 2020 : 1659–1664. 11.

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Published

2024-05-15

How to Cite

Ms. Renu ,Dr. Rajat Kumar. (2024). A Research based on Predicting Software Project Outcomes and Skill Gaps using Machine Learning . Journal of Computational Analysis and Applications (JoCAAA), 33(05), 1873–1883. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/2977

Issue

Vol. 33 No. 05 (2024): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.