Perspectives On Data Science For Software Engineering

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Perspectives on Data Science for Software Engineering

Author : Tim Menzies
Publisher : Morgan Kaufmann
ISBN 13 : 0128042613
Total Pages : 408 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Perspectives on Data Science for Software Engineering by : Tim Menzies

Download or read book Perspectives on Data Science for Software Engineering written by Tim Menzies and published by Morgan Kaufmann. This book was released on 2016-07-14 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Sathiyamoorthi, V.
Publisher : IGI Global
ISBN 13 : 179982568X
Total Pages : 324 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Challenges and Applications of Data Analytics in Social Perspectives by : Sathiyamoorthi, V.

Download or read book Challenges and Applications of Data Analytics in Social Perspectives written by Sathiyamoorthi, V. and published by IGI Global. This book was released on 2020-12-04 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Doing Data Science

Author : Cathy O'Neil
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 144936389X
Total Pages : 408 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis Doing Data Science by : Cathy O'Neil

Download or read book Doing Data Science written by Cathy O'Neil and published by "O'Reilly Media, Inc.". This book was released on 2013-10-09 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.

Contemporary Empirical Methods in Software Engineering

Author : Michael Felderer
Publisher : Springer Nature
ISBN 13 : 3030324893
Total Pages : 525 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Contemporary Empirical Methods in Software Engineering by : Michael Felderer

Download or read book Contemporary Empirical Methods in Software Engineering written by Michael Felderer and published by Springer Nature. This book was released on 2020-08-27 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Software Engineering Perspectives in Intelligent Systems

Author : Radek Silhavy
Publisher : Springer Nature
ISBN 13 : 3030633225
Total Pages : 1167 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Software Engineering Perspectives in Intelligent Systems by : Radek Silhavy

Download or read book Software Engineering Perspectives in Intelligent Systems written by Radek Silhavy and published by Springer Nature. This book was released on 2020-12-15 with total page 1167 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

New Perspectives in Software Engineering

Author : Jezreel Mejia
Publisher : Springer Nature
ISBN 13 : 3031203224
Total Pages : 324 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis New Perspectives in Software Engineering by : Jezreel Mejia

Download or read book New Perspectives in Software Engineering written by Jezreel Mejia and published by Springer Nature. This book was released on 2022-10-29 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Agile Data Science

Author : Russell Jurney
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449326927
Total Pages : 177 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis Agile Data Science by : Russell Jurney

Download or read book Agile Data Science written by Russell Jurney and published by "O'Reilly Media, Inc.". This book was released on 2013-10-15 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mining big data requires a deep investment in people and time. How can you be sure you’re building the right models? With this hands-on book, you’ll learn a flexible toolset and methodology for building effective analytics applications with Hadoop. Using lightweight tools such as Python, Apache Pig, and the D3.js library, your team will create an agile environment for exploring data, starting with an example application to mine your own email inboxes. You’ll learn an iterative approach that enables you to quickly change the kind of analysis you’re doing, depending on what the data is telling you. All example code in this book is available as working Heroku apps. Create analytics applications by using the agile big data development methodology Build value from your data in a series of agile sprints, using the data-value stack Gain insight by using several data structures to extract multiple features from a single dataset Visualize data with charts, and expose different aspects through interactive reports Use historical data to predict the future, and translate predictions into action Get feedback from users after each sprint to keep your project on track

Microservices in Big Data Analytics

Author : Anil Chaudhary
Publisher : Springer Nature
ISBN 13 : 9811501289
Total Pages : 206 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Microservices in Big Data Analytics by : Anil Chaudhary

Download or read book Microservices in Big Data Analytics written by Anil Chaudhary and published by Springer Nature. This book was released on 2019-11-26 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: These proceedings gather cutting-edge papers exploring the principles, techniques, and applications of Microservices in Big Data Analytics. The ICETCE-2019 is the latest installment in a successful series of annual conferences that began in 2011. Every year since, it has significantly contributed to the research community in the form of numerous high-quality research papers. This year, the conference’s focus was on the highly relevant area of Microservices in Big Data Analytics.

Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry

Author : Chkoniya, Valentina
Publisher : IGI Global
ISBN 13 : 1799869865
Total Pages : 653 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry by : Chkoniya, Valentina

Download or read book Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry written by Chkoniya, Valentina and published by IGI Global. This book was released on 2021-06-25 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.

Agile Data Science 2.0

Author : Russell Jurney
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 149196006X
Total Pages : 352 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Agile Data Science 2.0 by : Russell Jurney

Download or read book Agile Data Science 2.0 written by Russell Jurney and published by "O'Reilly Media, Inc.". This book was released on 2017-06-07 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data science teams looking to turn research into useful analytics applications require not only the right tools, but also the right approach if they’re to succeed. With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools. Author Russell Jurney demonstrates how to compose a data platform for building, deploying, and refining analytics applications with Apache Kafka, MongoDB, ElasticSearch, d3.js, scikit-learn, and Apache Airflow. You’ll learn an iterative approach that lets you quickly change the kind of analysis you’re doing, depending on what the data is telling you. Publish data science work as a web application, and affect meaningful change in your organization. Build value from your data in a series of agile sprints, using the data-value pyramid Extract features for statistical models from a single dataset Visualize data with charts, and expose different aspects through interactive reports Use historical data to predict the future via classification and regression Translate predictions into actions Get feedback from users after each sprint to keep your project on track

Analyzing the Analyzers

Author : Harlan Harris
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449368409
Total Pages : 55 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis Analyzing the Analyzers by : Harlan Harris

Download or read book Analyzing the Analyzers written by Harlan Harris and published by "O'Reilly Media, Inc.". This book was released on 2013-06-10 with total page 55 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite the excitement around "data science," "big data," and "analytics," the ambiguity of these terms has led to poor communication between data scientists and organizations seeking their help. In this report, authors Harlan Harris, Sean Murphy, and Marck Vaisman examine their survey of several hundred data science practitioners in mid-2012, when they asked respondents how they viewed their skills, careers, and experiences with prospective employers. The results are striking. Based on the survey data, the authors found that data scientists today can be clustered into four subgroups, each with a different mix of skillsets. Their purpose is to identify a new, more precise vocabulary for data science roles, teams, and career paths. This report describes: Four data scientist clusters: Data Businesspeople, Data Creatives, Data Developers, and Data Researchers Cases in miscommunication between data scientists and organizations looking to hire Why "T-shaped" data scientists have an advantage in breadth and depth of skills How organizations can apply the survey results to identify, train, integrate, team up, and promote data scientists

Artificial Intelligence Methods For Software Engineering

Author : Meir Kalech
Publisher : World Scientific
ISBN 13 : 9811239932
Total Pages : 457 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Artificial Intelligence Methods For Software Engineering by : Meir Kalech

Download or read book Artificial Intelligence Methods For Software Engineering written by Meir Kalech and published by World Scientific. This book was released on 2021-06-15 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: Software is an integral part of our lives today. Modern software systems are highly complex and often pose new challenges in different aspects of Software Engineering (SE).Artificial Intelligence (AI) is a growing field in computer science that has been proven effective in applying and developing AI techniques to address various SE challenges.This unique compendium covers applications of state-of-the-art AI techniques to the key areas of SE (design, development, debugging, testing, etc).All the materials presented are up-to-date. This reference text will benefit researchers, academics, professionals, and postgraduate students in AI, machine learning and software engineering.Related Link(s)

Optimising the Software Development Process with Artificial Intelligence

Author : José Raúl Romero
Publisher : Springer Nature
ISBN 13 : 9811999481
Total Pages : 349 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Optimising the Software Development Process with Artificial Intelligence by : José Raúl Romero

Download or read book Optimising the Software Development Process with Artificial Intelligence written by José Raúl Romero and published by Springer Nature. This book was released on 2023-07-19 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a practical introduction to the use of artificial intelligence (AI) techniques to improve and optimise the various phases of the software development process, from the initial project planning to the latest deployment. All chapters were written by leading experts in the field and include practical and reproducible examples. Following the introductory chapter, Chapters 2-9 respectively apply AI techniques to the classic phases of the software development process: project management, requirement engineering, analysis and design, coding, cloud deployment, unit and system testing, and maintenance. Subsequently, Chapters 10 and 11 provide foundational tutorials on the AI techniques used in the preceding chapters: metaheuristics and machine learning. Given its scope and focus, the book represents a valuable resource for researchers, practitioners and students with a basic grasp of software engineering.

Rethinking Productivity in Software Engineering

Author : Caitlin Sadowski
Publisher : Apress
ISBN 13 : 1484242211
Total Pages : 306 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Rethinking Productivity in Software Engineering by : Caitlin Sadowski

Download or read book Rethinking Productivity in Software Engineering written by Caitlin Sadowski and published by Apress. This book was released on 2019-05-07 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get the most out of this foundational reference and improve the productivity of your software teams. This open access book collects the wisdom of the 2017 "Dagstuhl" seminar on productivity in software engineering, a meeting of community leaders, who came together with the goal of rethinking traditional definitions and measures of productivity. The results of their work, Rethinking Productivity in Software Engineering, includes chapters covering definitions and core concepts related to productivity, guidelines for measuring productivity in specific contexts, best practices and pitfalls, and theories and open questions on productivity. You'll benefit from the many short chapters, each offering a focused discussion on one aspect of productivity in software engineering. Readers in many fields and industries will benefit from their collected work. Developers wanting to improve their personal productivity, will learn effective strategies for overcoming common issues that interfere with progress. Organizations thinking about building internal programs for measuring productivity of programmers and teams will learn best practices from industry and researchers in measuring productivity. And researchers can leverage the conceptual frameworks and rich body of literature in the book to effectively pursue new research directions. What You'll LearnReview the definitions and dimensions of software productivity See how time management is having the opposite of the intended effect Develop valuable dashboards Understand the impact of sensors on productivity Avoid software development waste Work with human-centered methods to measure productivity Look at the intersection of neuroscience and productivity Manage interruptions and context-switching Who Book Is For Industry developers and those responsible for seminar-style courses that include a segment on software developer productivity. Chapters are written for a generalist audience, without excessive use of technical terminology.

Software Engineering Perspectives in Systems

Author : Radek Silhavy
Publisher : Springer Nature
ISBN 13 : 3031090705
Total Pages : 769 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Software Engineering Perspectives in Systems by : Radek Silhavy

Download or read book Software Engineering Perspectives in Systems written by Radek Silhavy and published by Springer Nature. This book was released on 2022-07-16 with total page 769 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Software Engineering for Data Scientists

Author : Catherine Nelson
Publisher :
ISBN 13 : 9781098136208
Total Pages : 0 pages
Book Rating : 4.1/5 (362 download)

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Book Synopsis Software Engineering for Data Scientists by : Catherine Nelson

Download or read book Software Engineering for Data Scientists written by Catherine Nelson and published by . This book was released on 2024-10 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data science happens in code. The ability to write reproducible, robust, scaleable code is key to a data science project's success--and is absolutely essential for those working with production code. This practical book bridges the gap between data science and software engineering, clearly explaining how to apply the best practices from software engineering to data science. Examples are provided in Python, drawn from popular packages such as NumPy and pandas. If you want to write better data science code, this guide covers the essential topics you need (and that are often missing from introductory data science or coding classes), including how to: Understand data structures and object-oriented programming Clearly and skillfully document your code Package and share your code Integrate data science code with a larger codebase Write APIs Create secure code Apply best practices to common tasks such as testing, error handling, and logging Work more effectively with software engineers Write more efficient, maintainable, and robust code in Python Put your data science projects into production And more

Data Science in Engineering and Management

Author : Zdzislaw Polkowski
Publisher : CRC Press
ISBN 13 : 1000520846
Total Pages : 159 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Data Science in Engineering and Management by : Zdzislaw Polkowski

Download or read book Data Science in Engineering and Management written by Zdzislaw Polkowski and published by CRC Press. This book was released on 2021-12-31 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.