Leveraging Machine Learning To Improve Software Reliability
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| Author | : Roger Lee (Editor of Emotional artificial intelligence and metaverse) |
| Publisher | : Springer Nature |
| Total Pages | : 178 |
| Release | : |
| Genre | : Artificial intelligence |
| ISBN | : 3031563883 |
This book reports state-of-the-art results in Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. This edited book presents original papers on both theory and practice. It addresses foundations, state-of-the-art problems and solutions, and crucial challenges.
| Author | : Dr. Prakash Arumugam |
| Publisher | : Inkbound Publishers |
| Total Pages | : 291 |
| Release | : 2021-02-10 |
| Genre | : Computers |
| ISBN | : 8196822308 |
Embark on an extraordinary journey through the cutting-edge world of artificial intelligence with The Algorithmic Odyssey. This comprehensive guide serves as both a map and a compass for navigating the complex and rapidly evolving landscape of AI research. From the foundational principles of machine learning to the latest advancements in neural networks, this book offers a detailed exploration of the algorithms that are reshaping our world. Whether you are a seasoned researcher, a curious student, or a tech enthusiast, The Algorithmic Odyssey provides invaluable insights into the methodologies, challenges, and breakthroughs that define contemporary AI research. Discover the intricacies of supervised and unsupervised learning, delve into the depths of deep learning, and understand the transformative impact of reinforcement learning. Each chapter is meticulously crafted to offer clear explanations, practical examples, and thought-provoking discussions, making complex concepts accessible without sacrificing depth. Beyond the technicalities, The Algorithmic Odyssey also addresses the ethical, societal, and philosophical implications of AI. What does it mean to create intelligent systems? How do we ensure that these technologies benefit humanity? These questions and more are explored with rigor and sensitivity, encouraging readers to think critically about the future of AI. With contributions from leading experts in the field and a wealth of resources for further study, The Algorithmic Odyssey is an essential addition to the library of anyone passionate about the future of technology and its impact on our world. Join us on this odyssey and unlock the mysteries of artificial intelligence.
| Author | : Christian Bird |
| Publisher | : Elsevier |
| Total Pages | : 673 |
| Release | : 2015-09-02 |
| Genre | : Computers |
| ISBN | : 0124115438 |
The Art and Science of Analyzing Software Data provides valuable information on analysis techniques often used to derive insight from software data. This book shares best practices in the field generated by leading data scientists, collected from their experience training software engineering students and practitioners to master data science. The book covers topics such as the analysis of security data, code reviews, app stores, log files, and user telemetry, among others. It covers a wide variety of techniques such as co-change analysis, text analysis, topic analysis, and concept analysis, as well as advanced topics such as release planning and generation of source code comments. It includes stories from the trenches from expert data scientists illustrating how to apply data analysis in industry and open source, present results to stakeholders, and drive decisions. - Presents best practices, hints, and tips to analyze data and apply tools in data science projects - Presents research methods and case studies that have emerged over the past few years to further understanding of software data - Shares stories from the trenches of successful data science initiatives in industry
| Author | : P. K. Kapur |
| Publisher | : Springer Nature |
| Total Pages | : 391 |
| Release | : |
| Genre | : |
| ISBN | : 303155048X |
| Author | : Prakash Maharaj |
| Publisher | : The Write Order Publication |
| Total Pages | : 322 |
| Release | : 2024-06-18 |
| Genre | : Computers |
| ISBN | : 935776352X |
Prakash is an accomplished professional with over 20 years of experience working in various Software as a Service (SaaS) organizations. He has held leadership positions in the industry, demonstrating his expertise in managing teams, developing and implementing strategies, and driving business growth. Prakash is highly educated, with a Master's degree in Computers from Pune University, an MBA from the prestigious Indian Institute of Management (IIM) Calcutta, and a Ph.D. degree in management. This educational background has provided him with a strong foundation in both technical and management skills, making him well-equipped to understand the complexities of the SaaS industry and lead his teams to success. Prakash's experience and knowledge in the SaaS industry have enabled him to make significant contributions to the companies he has worked with. He has been instrumental in developing innovative products, improving operational efficiencies, and driving revenue growth. His ability to build strong relationships with clients and stakeholders has also helped him establish a solid reputation in the industry. Overall, Prakash's extensive experience, education, and leadership skills make him a valuable asset to any organization operating in the SaaS industry.
| Author | : Mihir Narayan Mohanty |
| Publisher | : Springer Nature |
| Total Pages | : 368 |
| Release | : 2022-10-17 |
| Genre | : Technology & Engineering |
| ISBN | : 3031117131 |
This book discusses an integration of machine learning with metaheuristic techniques that provide more robust and efficient ways to address traditional optimization problems. Modern metaheuristic techniques, along with their main characteristics and recent applications in artificial intelligence, software engineering, data mining, planning and scheduling, logistics and supply chains, are discussed in this book and help global leaders in fast decision making by providing quality solutions to important problems in business, engineering, economics and science. Novel ways are also discovered to attack unsolved problems in software testing and machine learning. The discussion on foundations of optimization and algorithms leads beginners to apply current approaches to optimization problems. The discussed metaheuristic algorithms include genetic algorithms, simulated annealing, ant algorithms, bee algorithms and particle swarm optimization. New developments on metaheuristics attract researchers and practitioners to apply hybrid metaheuristics in real scenarios.
| Author | : Farooq, Muhammad |
| Publisher | : IGI Global |
| Total Pages | : 402 |
| Release | : 2024-10-11 |
| Genre | : Computers |
| ISBN | : |
The transformative impacts of artificial intelligence (AI) in management are reshaping organizational dynamics and redefining traditional leadership roles. By harnessing AI technologies, companies are achieving higher levels of efficiency, insight, and strategic agility. AI-powered tools facilitate data-driven decision-making, automate routine tasks, and enhance predictive analytics, enabling managers to focus on high-value activities and strategic innovation. From optimizing supply chains and personalizing customer interactions to streamlining human resources and financial planning, AI is driving changes across all aspects of management. As businesses embrace these advancements, further research is necessary to improve operational performance and position businesses for long-term success. Transformative Impacts of AI in Management delves into the transformative impact of AI across management science, education, business, marketing, and agriculture. Through a structured synthesis of literature, the publication provides a detailed analysis of applications, challenges, and opportunities in each domain. This book covers topics such as management science, artificial intelligence, and marketing, and is a useful resource for academicians, policymakers, business owners, computer engineers, agriculturalists, educators, scientists, and researchers.
| Author | : Dr R. Keerthika |
| Publisher | : Inkbound Publishers |
| Total Pages | : 224 |
| Release | : 2022-01-20 |
| Genre | : Computers |
| ISBN | : 8196822340 |
Delve into the fascinating world of machine learning with this comprehensive guide, which unpacks the algorithms driving today's intelligent systems. From foundational concepts to advanced applications, this book is essential for anyone looking to understand the mechanics behind AI.
| Author | : El Bachir Boukherouaa |
| Publisher | : International Monetary Fund |
| Total Pages | : 35 |
| Release | : 2021-10-22 |
| Genre | : Business & Economics |
| ISBN | : 1589063953 |
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
| Author | : Marc Peter Deisenroth |
| Publisher | : Cambridge University Press |
| Total Pages | : 392 |
| Release | : 2020-04-23 |
| Genre | : Computers |
| ISBN | : 1108569323 |
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
