Perspectives on Data Science for Software Engineering Book
Score: 5
From 1 Ratings

Perspectives on Data Science for Software Engineering


  • Author : Tim Menzies
  • Publisher : Morgan Kaufmann
  • Release Date : 2016-07-14
  • Genre: Computers
  • Pages : 408
  • ISBN 10 : 9780128042618

GET BOOK
Perspectives on Data Science for Software Engineering 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

Contemporary Empirical Methods in Software Engineering Book

Contemporary Empirical Methods in Software Engineering


  • Author : Michael Felderer
  • Publisher : Springer Nature
  • Release Date : 2020-08-27
  • Genre: Computers
  • Pages : 525
  • ISBN 10 : 9783030324896

GET BOOK
Contemporary Empirical Methods in Software Engineering 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.

Build a Career in Data Science Book

Build a Career in Data Science


  • Author : Emily Robinson
  • Publisher : Simon and Schuster
  • Release Date : 2020-03-06
  • Genre: Computers
  • Pages : 354
  • ISBN 10 : 9781638350156

GET BOOK
Build a Career in Data Science Excerpt :

Summary You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology What are the keys to a data scientist’s long-term success? Blending your technical know-how with the right “soft skills” turns out to be a central ingredient of a rewarding career. About the book Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee. By following clear and simple instructions, you’ll learn to craft an amazing resume and ace your interviews. In this demanding, rapidly changing field, it can be challenging to keep projects on track, adapt to company needs, and manage tricky stakeholders. You’ll love the insights on how to handle expectations, deal with failures, and plan your career path in the stories from seasoned data scientists included in the book. What's inside Creating a portfolio of data science projects Assessing and negotiating an offer Leaving gracefully and moving up the ladder Interviews with professional data scientists About the reader For readers who want to begin or advance a data science career. About the author Emily Robinson is a data scientist at Warby Parker. Jacqueline Nolis is a data science consultant and mentor. Table of Contents: PART 1 - GETTING STARTED WITH DATA SCIENCE 1. What is data science? 2. Data science companies 3. Getting the skills 4. Building a portfolio PART 2 - FINDING YOUR DATA SCIENCE JOB 5. The search: Identifying the right job for you 6. The application: Résumés and cover letters 7. The interview: What to expect and how to handle it 8. The offer: Knowing what to accept PART 3 - SETTLING INTO DATA SCIENCE 9. The first months on th

Agile Processes in Software Engineering and Extreme Programming     Workshops Book

Agile Processes in Software Engineering and Extreme Programming Workshops


  • Author : Rashina Hoda
  • Publisher : Springer Nature
  • Release Date : 2019-08-30
  • Genre: Computers
  • Pages : 159
  • ISBN 10 : 9783030301262

GET BOOK
Agile Processes in Software Engineering and Extreme Programming Workshops Excerpt :

This open access book constitutes the research workshops, doctoral symposium and panel summaries presented at the 20th International Conference on Agile Software Development, XP 2019, held in Montreal, QC, Canada, in May 2019. XP is the premier agile software development conference combining research and practice. It is a hybrid forum where agile researchers, academics, practitioners, thought leaders, coaches, and trainers get together to present and discuss their most recent innovations, research results, experiences, concerns, challenges, and trends. Following this history, for both researchers and seasoned practitioners XP 2019 provided an informal environment to network, share, and discover trends in Agile for the next 20 years. Research papers and talks submissions were invited for the three XP 2019 research workshops, namely, agile transformation, autonomous teams, and large scale agile. This book includes 15 related papers. In addition, a summary for each of the four panels at XP 2019 is included. The panels were on security and privacy; the impact of the agile manifesto on culture, education, and software practices; business agility – agile’s next frontier; and Agile – the next 20 years.

Microservices in Big Data Analytics Book

Microservices in Big Data Analytics


  • Author : Anil Chaudhary
  • Publisher : Springer Nature
  • Release Date : 2019-11-26
  • Genre: Computers
  • Pages : 188
  • ISBN 10 : 9789811501289

GET BOOK
Microservices in Big Data Analytics 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.

Doing Data Science Book
Score: 4
From 1 Ratings

Doing Data Science


  • Author : Cathy O'Neil
  • Publisher : "O'Reilly Media, Inc."
  • Release Date : 2013-10-09
  • Genre: Computers
  • Pages : 408
  • ISBN 10 : 9781449363895

GET BOOK
Doing Data Science 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.

Software Engineering Perspectives in Intelligent Systems Book

Software Engineering Perspectives in Intelligent Systems


  • Author : Radek Silhavy
  • Publisher : Springer Nature
  • Release Date : 2020-12-15
  • Genre: Technology & Engineering
  • Pages : 1150
  • ISBN 10 : 9783030633226

GET BOOK
Software Engineering Perspectives in Intelligent Systems 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.

Agile Data Science 2 0 Book

Agile Data Science 2 0


  • Author : Russell Jurney
  • Publisher : "O'Reilly Media, Inc."
  • Release Date : 2017-06-07
  • Genre: Computers
  • Pages : 352
  • ISBN 10 : 9781491960066

GET BOOK
Agile Data Science 2 0 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

Artificial Intelligence Methods For Software Engineering Book

Artificial Intelligence Methods For Software Engineering


  • Author : Meir Kalech
  • Publisher : World Scientific
  • Release Date : 2021-06-15
  • Genre: Computers
  • Pages : 456
  • ISBN 10 : 9789811239939

GET BOOK
Artificial Intelligence Methods For Software Engineering 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)

Rethinking Productivity in Software Engineering Book

Rethinking Productivity in Software Engineering


  • Author : Caitlin Sadowski
  • Publisher : Apress
  • Release Date : 2019-05-07
  • Genre: Computers
  • Pages : 310
  • ISBN 10 : 9781484242216

GET BOOK
Rethinking Productivity in Software Engineering 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.

Computational Management Book

Computational Management


  • Author : Srikanta Patnaik
  • Publisher : Springer Nature
  • Release Date : 2021-05-29
  • Genre: Technology & Engineering
  • Pages : 682
  • ISBN 10 : 9783030729295

GET BOOK
Computational Management Excerpt :

This book offers a timely review of cutting-edge applications of computational intelligence to business management and financial analysis. It covers a wide range of intelligent and optimization techniques, reporting in detail on their application to real-world problems relating to portfolio management and demand forecasting, decision making, knowledge acquisition, and supply chain scheduling and management.

Agile Data Science Book

Agile Data Science


  • Author : Russell Jurney
  • Publisher : "O'Reilly Media, Inc."
  • Release Date : 2013-10-15
  • Genre: COMPUTERS
  • Pages : 178
  • ISBN 10 : 9781449326920

GET BOOK
Agile Data Science 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

Software Design for Engineers and Scientists Book

Software Design for Engineers and Scientists


  • Author : John Allen Robinson
  • Publisher : Elsevier
  • Release Date : 2004-08-21
  • Genre: Computers
  • Pages : 414
  • ISBN 10 : 0080474403

GET BOOK
Software Design for Engineers and Scientists Excerpt :

Software Design for Engineers and Scientists integrates three core areas of computing: . Software engineering - including both traditional methods and the insights of 'extreme programming' . Program design - including the analysis of data structures and algorithms . Practical object-oriented programming Without assuming prior knowledge of any particular programming language, and avoiding the need for students to learn from separate, specialised Computer Science texts, John Robinson takes the reader from small-scale programing to competence in large software projects, all within one volume. Copious examples and case studies are provided in C++. The book is especially suitable for undergraduates in the natural sciences and all branches of engineering who have some knowledge of computing basics, and now need to understand and apply software design to tasks like data analysis, simulation, signal processing or visualisation. John Robinson introduces both software theory and its application to problem solving using a range of design principles, applied to the creation of medium-sized systems, providing key methods and tools for designing reliable, efficient, maintainable programs. The case studies are presented within scientific contexts to illustrate all aspects of the design process, allowing students to relate theory to real-world applications. Core computing topics - usually found in separate specialised texts - presented to meet the specific requirements of science and engineering students Demonstrates good practice through applications, case studies and worked examples based in real-world contexts

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

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


  • Author : Chkoniya, Valentina
  • Publisher : IGI Global
  • Release Date : 2021-06-25
  • Genre: Computers
  • Pages : 653
  • ISBN 10 : 9781799869863

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

Advances in Information Systems Development Book

Advances in Information Systems Development


  • Author : Bo Andersson
  • Publisher : Springer
  • Release Date : 2019-08-02
  • Genre: Computers
  • Pages : 264
  • ISBN 10 : 9783030229931

GET BOOK
Advances in Information Systems Development Excerpt :

This volume features a collection of papers on emerging concepts, significant insights, novel approaches and ideas in information systems research. It examines advances in information systems development in general, and their impact on the development of new methods, tools and management. The book contains invited papers selected from the 27th International Conference on Information Systems Development (ISD) held in Lund, Sweden, August 22 - 24, 2018. The revised and expanded papers present research that focuses on methods, tools and management in information systems development. These issues are significant as they provide the basis for organizations to identify new markets, support innovative technology deployment, and enable mobile applications to detect, sense, interpret and respond to the environment.