Advancing Software Engineering in the AI-ML Paradigm: A Study of Optimized Methodologies and Obstacles
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2023
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| _version_ | 1866901358948384768 |
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| author | Dr. Rohan Jain and Dr. Leela Rao |
| author_facet | Dr. Rohan Jain and Dr. Leela Rao |
| contents | <p>In the rapidly evolving landscape of software engineering, the integration of artificial intelligence (AI) and machine learning (ML) technologies presents both opportunities and challenges. This paper explores the best practices and challenges associated with leveraging AI and ML in software engineering processes. We discuss the importance of efficient software engineering practices in the era of AI and ML, highlighting key considerations such as data management, algorithm selection, model deployment, and ethical considerations. By addressing these challenges and adopting best practices, software engineers can harness the power of AI and ML to develop robust and scalable software solutions that meet the evolving needs of modern organizations.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19330990 |
| institution | Zenodo |
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| publishDate | 2023 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Advancing Software Engineering in the AI-ML Paradigm: A Study of Optimized Methodologies and Obstacles Dr. Rohan Jain and Dr. Leela Rao Software Engineering Artificial Intelligence Machine Learning Best Practices Challenges Introduction: <p>In the rapidly evolving landscape of software engineering, the integration of artificial intelligence (AI) and machine learning (ML) technologies presents both opportunities and challenges. This paper explores the best practices and challenges associated with leveraging AI and ML in software engineering processes. We discuss the importance of efficient software engineering practices in the era of AI and ML, highlighting key considerations such as data management, algorithm selection, model deployment, and ethical considerations. By addressing these challenges and adopting best practices, software engineers can harness the power of AI and ML to develop robust and scalable software solutions that meet the evolving needs of modern organizations.</p> |
| title | Advancing Software Engineering in the AI-ML Paradigm: A Study of Optimized Methodologies and Obstacles |
| topic | Software Engineering Artificial Intelligence Machine Learning Best Practices Challenges Introduction: |
| url | https://doi.org/10.5281/zenodo.19330990 |