Perspectives on Data Science for Software Engineering

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  • Author : Tim Menzies
  • Publisher : Morgan Kaufmann
  • Pages : 408 pages
  • ISBN : 0128042613
  • Rating : 5/5 from 1 reviews
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Download or Read online Perspectives on Data Science for Software Engineering full in PDF, ePub and kindle. this book written by Tim Menzies and published by Morgan Kaufmann which was released on 14 July 2016 with total page 408 pages. We cannot guarantee that Perspectives on Data Science for Software Engineering book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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

Perspectives on Data Science for Software Engineering

Perspectives on Data Science for Software Engineering
  • Author : Tim Menzies,Laurie Williams,Thomas Zimmermann
  • Publisher : Morgan Kaufmann
  • Release : 14 July 2016
GET THIS BOOK Perspectives on Data Science for Software Engineering

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

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Software Engineering Perspectives and Application in Intelligent Systems
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  • Publisher : Springer
  • Release : 21 April 2016
GET THIS BOOK Software Engineering Perspectives and Application in Intelligent Systems

The volume Software Engineering Perspectives and Application in Intelligent Systems presents new approaches and methods to real-world problems, and in particular, exploratory research that describes novel approaches in the field of Software Engineering. Particular emphasis is laid on modern trends in selected fields of interest. New algorithms or methods in a variety of fields are also presented. The 5th Computer Science On-line Conference (CSOC 2016) is intended to provide an international forum for discussions on the latest research results in all

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  • Publisher : IGI Global
  • Release : 04 December 2020
GET THIS BOOK Challenges and Applications of Data Analytics in Social Perspectives

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

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  • Publisher : Springer
  • Release : 08 August 2017
GET THIS BOOK The Data Science Design Manual

This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book

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  • Publisher : John Wiley & Sons
  • Release : 13 April 2021
GET THIS BOOK Responsible Data Science

Explore the most serious prevalent ethical issues in data science with this insightful new resource The increasing popularity of data science has resulted in numerous well-publicized cases of bias, injustice, and discrimination. The widespread deployment of “Black box” algorithms that are difficult or impossible to understand and explain, even for their developers, is a primary source of these unanticipated harms, making modern techniques and methods for manipulating large data sets seem sinister, even dangerous. When put in the hands of

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  • Publisher : Springer
  • Release : 01 July 2003
GET THIS BOOK Computer Science in Perspective

By presenting state-of-the-art aspects of theoretical computer science and practical applications in various fields, this book commemorates the 60th birthday of Thomas Ottmann. The 26 research papers presented span the whole range of Thomas Ottmann's scientific career, from formal languages to algorithms and data structures, from topics in practical computer science like software engineering or database systems to applications of Web technology, groupware, and e-learning.

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Business Intelligence Strategy and Big Data Analytics
  • Author : Steve Williams
  • Publisher : Morgan Kaufmann
  • Release : 08 April 2016
GET THIS BOOK Business Intelligence Strategy and Big Data Analytics

Business Intelligence Strategy and Big Data Analytics is written for business leaders, managers, and analysts - people who are involved with advancing the use of BI at their companies or who need to better understand what BI is and how it can be used to improve profitability. It is written from a general management perspective, and it draws on observations at 12 companies whose annual revenues range between $500 million and $20 billion. Over the past 15 years, my company has formulated vendor-neutral business-focused

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Perspectives on Software Documentation
  • Author : Thomas T. Barker
  • Publisher : Routledge
  • Release : 13 June 1991
GET THIS BOOK Perspectives on Software Documentation

This book is designed to address the randomness of the literature on software documentation. As anyone interested in software documentation is aware, the field is highly synthetic; information about software documentation may be found in engineering, computer science training, technical communication, management, education and so on. "Perspectives on Software Documentation" contains a variety of perspectives, all tied together by the shared need to make software products more usable.

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  • Author : Zaigham Mahmood
  • Publisher : Springer
  • Release : 05 July 2016
GET THIS BOOK Data Science and Big Data Computing

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

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  • Author : Brian Godsey
  • Publisher : Manning Publications
  • Release : 28 February 2017
GET THIS BOOK Think Like a Data Scientist

Data science is more than just a set of tools and techniques for extracting knowledge from data sets and data streams. Data science is also a process of getting from goals and questions to real, valuable outcomes by exploring, observing, and manipulating a world of data. Traversing this world can be difficult and confusing. Software developers and non-technical folks may struggle with the uncertainty and fuzzy answers that data invariably provide, and statisticians may have trouble working with any of

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Software Engineering Foundations
  • Author : Yingxu Wang
  • Publisher : CRC Press
  • Release : 09 August 2007
GET THIS BOOK Software Engineering Foundations

A groundbreaking book in this field, Software Engineering Foundations: A Software Science Perspective integrates the latest research, methodologies, and their applications into a unified theoretical framework. Based on the author's 30 years of experience, it examines a wide range of underlying theories from philosophy, cognitive informatics, denota