博客來Machine Learning for Software Engineering: Techniques, Tools, and Applications＂ is a comprehensive guide that delves into the transformative potential of machine learning in the field of software engineering. From leveraging predictive analytics to improve software quality and reliability to optimizing development processes through data-driven insights, this book offers a deep dive into the latest techniques, tools, and applications shaping the future of software development.
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Machine Learning for SE: Techniques, Tools, and Applications 作者：Saraswat 出版社：LAP Lambert Academic Publishing 出版日期：2024-04-04 語言：英文 規格：平裝 / 60頁 / 22.86 x 15.24 x 0.36 cm / 普通級/ 初版 |
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圖書名稱：Machine Learning for SE: Techniques, Tools, and Applications
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Control Theory for Practical Applications: With MATLAB Demonstration Programs
Food Security, Nutrition and Sustainability Through Aquaculture Technologies
Novel Nanocarriers for Skin Diseases: Advances and Applications
Advances in Autonomous Navigation Through Intelligent Technologies
Nonthermal Light-Based Technologies in Food Processing
Advances in Computational Intelligence Systems: Contributions Presented at the 23rd UK Workshop on Computational Intelligence (Ukci 2024), September 2
The Amateur Plankton Researcher’s Practical Guide: How to Study Plankton at Home
The Challenges of Era 5.0 in Accounting and Finance Innovation
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