[Download] Boosting Software Development Using Machine Learning PDF EPUB

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Boosting Software Development Using Machine Learning Summary

Boosting Software Development Using Machine Learning is a beautiful novel written by Tirimula Rao Benala. The book was published on May 24, 2025 and is available in both PDF and EPUB formats. Below is the summary of “Boosting Software Development Using Machine Learning by Tirimula Rao Benala”:

This book explores the transformative effects of AI and ML on software engineering. It emphasizes the potential of cutting-edge software development technologies such as Generative AI and ML applications. This book incorporates data-driven strategies across the entire software development life cycle, from requirements elicitation and design to coding, testing, and deployment. It illustrates the evolution from traditional frameworks to agile and DevOps methodologies. The potential of Generative AI for automating repetitive tasks and enhancing code quality is highlighted, along with ML applications in optimizing testing, effort estimation, design pattern recognition, fault prediction, debugging, and security through anomaly detection. These techniques have significantly improved software development efficiency, predictability, and project management effectiveness. While remarkable progress has been made, much remains to be done in this evolving area. This edited book is a timely effort toward advancing the field and promoting interdisciplinary collaboration in addressing ethical, security, and technical challenges.

Details About Boosting Software Development Using Machine Learning by Tirimula Rao Benala

• Title: Boosting Software Development Using Machine Learning
• Author: Tirimula Rao Benala
• Language: English
• Genres:
• Series:
• Published Date: May 24, 2025
• Status: Available for Download
• Formats: PDF/EPUB
• [EPUB] Filename: Boosting_Software_Development_Using_ML_-_Tirimula_Rao_Benala.epub
• [PDF] Filename: Boosting_Software_Development_Using_ML_-_Tirimula_Rao_Benala.pdf
• EPUB File Size: 14.71 MB
• PDF File Size: 18.84 MB

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