Perspectives On Data Science For Software Engineering
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Perspectives On Data Science For Software Engineering
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Author : Tim Menzies
language : en
Publisher: Morgan Kaufmann
Release Date : 2016-07-14
Perspectives On Data Science For Software Engineering written by Tim Menzies and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-14 with Computers categories.
Perspectives on Data Science for Software Engineering presents the best practices of seasoned data miners in software engineering. The idea for this book was created during the 2014 conference at Dagstuhl, an invitation-only gathering of leading computer scientists who meet to identify and discuss cutting-edge informatics topics. At the 2014 conference, the concept of how to transfer the knowledge of experts from seasoned software engineers and data scientists to newcomers in the field highlighted many discussions. While there are many books covering data mining and software engineering basics, they present only the fundamentals and lack the perspective that comes from real-world experience. This book offers unique insights into the wisdom of the community’s leaders gathered to share hard-won lessons from the trenches. Ideas are presented in digestible chapters designed to be applicable across many domains. Topics included cover data collection, data sharing, data mining, and how to utilize these techniques in successful software projects. Newcomers to software engineering data science will learn the tips and tricks of the trade, while more experienced data scientists will benefit from war stories that show what traps to avoid. Presents the wisdom of community experts, derived from a summit on software analytics Provides contributed chapters that share discrete ideas and technique from the trenches Covers top areas of concern, including mining security and social data, data visualization, and cloud-based data Presented in clear chapters designed to be applicable across many domains
Challenges And Applications Of Data Analytics In Social Perspectives
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Author : Sathiyamoorthi, V.
language : en
Publisher: IGI Global
Release Date : 2020-12-04
Challenges And Applications Of Data Analytics In Social Perspectives written by Sathiyamoorthi, V. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-04 with Computers categories.
With exponentially increasing amounts of data accumulating in real-time, there is no reason why one should not turn data into a competitive advantage. While machine learning, driven by advancements in artificial intelligence, has made great strides, it has not been able to surpass a number of challenges that still prevail in the way of better success. Such limitations as the lack of better methods, deeper understanding of problems, and advanced tools are hindering progress. Challenges and Applications of Data Analytics in Social Perspectives provides innovative insights into the prevailing challenges in data analytics and its application on social media and focuses on various machine learning and deep learning techniques in improving practice and research. The content within this publication examines topics that include collaborative filtering, data visualization, and edge computing. It provides research ideal for data scientists, data analysts, IT specialists, website designers, e-commerce professionals, government officials, software engineers, social media analysts, industry professionals, academicians, researchers, and students.
Data Science And Big Data Computing
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Author : Zaigham Mahmood
language : en
Publisher: Springer
Release Date : 2016-07-05
Data Science And Big Data Computing written by Zaigham Mahmood and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-05 with Business & Economics categories.
This illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. Expert perspectives are provided by authoritative researchers and practitioners from around the world, discussing research developments and emerging trends, presenting case studies on helpful frameworks and innovative methodologies, and suggesting best practices for efficient and effective data analytics. Features: reviews a framework for fast data applications, a technique for complex event processing, and agglomerative approaches for the partitioning of networks; introduces a unified approach to data modeling and management, and a distributed computing perspective on interfacing physical and cyber worlds; presents techniques for machine learning for big data, and identifying duplicate records in data repositories; examines enabling technologies and tools for data mining; proposes frameworks for data extraction, and adaptive decision making and social media analysis.
Software Engineering Perspectives In Intelligent Systems
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Author : Radek Silhavy
language : en
Publisher: Springer Nature
Release Date : 2020-12-15
Software Engineering Perspectives In Intelligent Systems written by Radek Silhavy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-15 with Technology & Engineering categories.
This book constitutes the refereed proceedings of the 4th Computational Methods in Systems and Software 2020 (CoMeSySo 2020) proceedings. Software engineering, computer science and artificial intelligence are crucial topics for the research within an intelligent systems problem domain. The CoMeSySo 2020 conference is breaking the barriers, being held online. CoMeSySo 2020 intends to provide an international forum for the discussion of the latest high-quality research results.
Data Science In Engineering And Management
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Author : Zdzislaw Polkowski
language : en
Publisher: CRC Press
Release Date : 2021-12-30
Data Science In Engineering And Management written by Zdzislaw Polkowski and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-30 with Technology & Engineering categories.
This book brings insight into data science and offers applications and implementation strategies. It includes current developments and future directions and covers the concept of data science along with its origins. It focuses on the mechanisms of extracting data along with classifications, architectural concepts, and business intelligence with predictive analysis. Data Science in Engineering and Management: Applications, New Developments, and Future Trends introduces the concept of data science, its use, and its origins, as well as presenting recent trends, highlighting future developments; discussing problems and offering solutions. It provides an overview of applications on data linked to engineering and management perspectives and also covers how data scientists, analysts, and program managers who are interested in productivity and improving their business can do so by incorporating a data science workflow effectively. This book is useful to researchers involved in data science and can be a reference for future research. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.
Think Like A Data Scientist
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Author : Brian Godsey
language : en
Publisher: Simon and Schuster
Release Date : 2017-03-09
Think Like A Data Scientist written by Brian Godsey and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-09 with Computers categories.
Summary Think Like a Data Scientist presents a step-by-step approach to data science, combining analytic, programming, and business perspectives into easy-to-digest techniques and thought processes for solving real world data-centric problems. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Data collected from customers, scientific measurements, IoT sensors, and so on is valuable only if you understand it. Data scientists revel in the interesting and rewarding challenge of observing, exploring, analyzing, and interpreting this data. Getting started with data science means more than mastering analytic tools and techniques, however; the real magic happens when you begin to think like a data scientist. This book will get you there. About the Book Think Like a Data Scientist teaches you a step-by-step approach to solving real-world data-centric problems. By breaking down carefully crafted examples, you'll learn to combine analytic, programming, and business perspectives into a repeatable process for extracting real knowledge from data. As you read, you'll discover (or remember) valuable statistical techniques and explore powerful data science software. More importantly, you'll put this knowledge together using a structured process for data science. When you've finished, you'll have a strong foundation for a lifetime of data science learning and practice. What's Inside The data science process, step-by-step How to anticipate problems Dealing with uncertainty Best practices in software and scientific thinking About the Reader Readers need beginner programming skills and knowledge of basic statistics. About the Author Brian Godsey has worked in software, academia, finance, and defense and has launched several data-centric start-ups. Table of Contents PART 1 - PREPARING AND GATHERING DATA AND KNOWLEDGE Philosophies of data science Setting goals by asking good questions Data all around us: the virtual wilderness Data wrangling: from capture to domestication Data assessment: poking and prodding PART 2 - BUILDING A PRODUCT WITH SOFTWARE AND STATISTICS Developing a plan Statistics and modeling: concepts and foundations Software: statistics in action Supplementary software: bigger, faster, more efficient Plan execution: putting it all together PART 3 - FINISHING OFF THE PRODUCT AND WRAPPING UP Delivering a product After product delivery: problems and revisions Wrapping up: putting the project away
New Perspectives In Software Engineering
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Author : Jezreel Mejia
language : en
Publisher: Springer Nature
Release Date : 2022-10-29
New Perspectives In Software Engineering written by Jezreel Mejia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-29 with Technology & Engineering categories.
This book contains the proceedings of the CIMPS Conference held on October 19-21, 2022, Hipócrates University, Acapulco de Juárez, Guerrero, México, that is dedicated to Software Engineering, in particular, software processes improvement, computer security and communication technology, artificial intelligence and data analysis (big data) with a focus on innovation and/or entrepreneurship, bringing together the academic sectors, governmental and industrial that promote the comprehensive development of a culture of research, innovation and competitiveness of organizations dedicated to and/or that make use of Information and Communication Telecommunications. This book presents software engineering with impact in a combination of different fields: Organizational Models, Standards and Methodologies, Knowledge Management, Software Systems, Applications and Tools, Information and Communication Technologies, Information security, Artificial intelligence, Data Analysis. It is used in different domains in which a broad scope of audience is interested in: • Software engineers • Analyst • Project management • Consultant • Professors in academia • Students • Corporate heads of firms • Senior general managers • Managing directors • Board directors • Academics and researchers in the field both in universities and business schools • Information technology directors and managers • Quality managers and directors • Libraries and information centres serving the needs of the above This book contents are also useful for Ph.D. students, master’s and undergraduate students of IT-related degrees such as Computer Science, Information Systems.
Software Engineering Perspectives In Systems
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Author : Radek Silhavy
language : en
Publisher: Springer Nature
Release Date : 2022-07-16
Software Engineering Perspectives In Systems written by Radek Silhavy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-16 with Technology & Engineering categories.
The study of software engineering and its applications to system engineering is critical in computer science research. Modern research methodologies, as well as the use of machine and statistical learning in software engineering research, are covered in this book. This book contains the refereed proceedings of the Software Engineering Perspectives in Systems part of the 11th Computer Science On-line Conference 2022 (CSOC 2022), which was held in April 2022 online.
Contemporary Empirical Methods In Software Engineering
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Author : Michael Felderer
language : en
Publisher: Springer Nature
Release Date : 2020-08-27
Contemporary Empirical Methods In Software Engineering written by Michael Felderer and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-27 with Computers categories.
This book presents contemporary empirical methods in software engineering related to the plurality of research methodologies, human factors, data collection and processing, aggregation and synthesis of evidence, and impact of software engineering research. The individual chapters discuss methods that impact the current evolution of empirical software engineering and form the backbone of future research. Following an introductory chapter that outlines the background of and developments in empirical software engineering over the last 50 years and provides an overview of the subsequent contributions, the remainder of the book is divided into four parts: Study Strategies (including e.g. guidelines for surveys or design science); Data Collection, Production, and Analysis (highlighting approaches from e.g. data science, biometric measurement, and simulation-based studies); Knowledge Acquisition and Aggregation (highlighting literature research, threats to validity, and evidence aggregation); and Knowledge Transfer (discussing open science and knowledge transfer with industry). Empirical methods like experimentation have become a powerful means of advancing the field of software engineering by providing scientific evidence on software development, operation, and maintenance, but also by supporting practitioners in their decision-making and learning processes. Thus the book is equally suitable for academics aiming to expand the field and for industrial researchers and practitioners looking for novel ways to check the validity of their assumptions and experiences. Chapter 17 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
The Art And Science Of Analyzing Software Data
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Author : Christian Bird
language : en
Publisher: Elsevier
Release Date : 2015-09-02
The Art And Science Of Analyzing Software Data written by Christian Bird and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-02 with Computers categories.
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