Download The Art And Science Of Analyzing Software Data Book PDF

Download full The Art And Science Of Analyzing Software Data books PDF, EPUB, Tuebl, Textbook, Mobi or read online The Art And Science Of Analyzing Software Data anytime and anywhere on any device. Get free access to the library by create an account, fast download and ads free. We cannot guarantee that every book is in the library.

The Art and Science of Analyzing Software Data

The Art and Science of Analyzing Software Data
  • Author : Christian Bird,Tim Menzies,Thomas Zimmermann
  • Publisher :Unknown
  • Release Date :2015-09-02
  • Total pages :672
  • ISBN : 9780124115439
GET BOOK HERE

Summary : 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

Contemporary Empirical Methods in Software Engineering

Contemporary Empirical Methods in Software Engineering
  • Author : Michael Felderer,Guilherme Horta Travassos
  • Publisher :Unknown
  • Release Date :2020
  • Total pages :525
  • ISBN : 9783030324896
GET BOOK HERE

Summary : 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.

Perspectives on Data Science for Software Engineering

Perspectives on Data Science for Software Engineering
  • Author : Tim Menzies,Laurie Williams,Thomas Zimmermann
  • Publisher :Unknown
  • Release Date :2016-07-14
  • Total pages :408
  • ISBN : 9780128042618
GET BOOK HERE

Summary : 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

Sharing Data and Models in Software Engineering

Sharing Data and Models in Software Engineering
  • Author : Tim Menzies,Ekrem Kocaguneli,Burak Turhan,Leandro Minku,Fayola Peters
  • Publisher :Unknown
  • Release Date :2014-12-22
  • Total pages :406
  • ISBN : 9780124173071
GET BOOK HERE

Summary : Data Science for Software Engineering: Sharing Data and Models presents guidance and procedures for reusing data and models between projects to produce results that are useful and relevant. Starting with a background section of practical lessons and warnings for beginner data scientists for software engineering, this edited volume proceeds to identify critical questions of contemporary software engineering related to data and models. Learn how to adapt data from other organizations to local problems, mine privatized data, prune spurious information, simplify complex results, how to update models for new platforms, and more. Chapters share largely applicable experimental results discussed with the blend of practitioner focused domain expertise, with commentary that highlights the methods that are most useful, and applicable to the widest range of projects. Each chapter is written by a prominent expert and offers a state-of-the-art solution to an identified problem facing data scientists in software engineering. Throughout, the editors share best practices collected from their experience training software engineering students and practitioners to master data science, and highlight the methods that are most useful, and applicable to the widest range of projects. Shares the specific experience of leading researchers and techniques developed to handle data problems in the realm of software engineering Explains how to start a project of data science for software engineering as well as how to identify and avoid likely pitfalls Provides a wide range of useful qualitative and quantitative principles ranging from very simple to cutting edge research Addresses current challenges with software engineering data such as lack of local data, access issues due to data privacy, increasing data quality via cleaning of spurious chunks in data

Data Science and Big Data Analytics

Data Science and Big Data Analytics
  • Author : EMC Education Services
  • Publisher :Unknown
  • Release Date :2015-01-05
  • Total pages :432
  • ISBN : 9781118876053
GET BOOK HERE

Summary : Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Corresponding data sets are available at www.wiley.com/go/9781118876138. Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!

The Art and Science of Technical Analysis

The Art and Science of Technical Analysis
  • Author : Adam Grimes
  • Publisher :Unknown
  • Release Date :2012-05-31
  • Total pages :480
  • ISBN : 9781118238141
GET BOOK HERE

Summary : A breakthrough trading book that provides powerful insights on profitable technical patterns and strategies The Art and Science of Technical Analysis is a groundbreaking work that bridges the gaps between the academic view of markets, technical analysis, and profitable trading. The book explores why randomness prevails in markets most, but not all, of the time and how technical analysis can be used to capture statistically validated patterns in certain types of market conditions. The belief of the book is that buying and selling pressure causes patterns in prices, but that these technical patterns are only effective in the presence of true buying/selling imbalance. The Art and Science of Technical Analysis is supported by extensive statistical analysis of the markets, which will debunk some tools and patterns such as Fibonacci analysis, and endorse other tools and trade setups. In addition, this reliable resource discusses trader psychology and trader learning curves based on the author's extensive experience as a trader and trainer of traders. Offers serious traders a way to think about market problems, understand their own performance, and help find a more productive path forward Includes extensive research to validate specific money-making patterns and strategies Written by an experienced market practitioner who has trained and worked with many top traders Filled with in-depth insights and practical advice, The Art and Science of Technical Analysis will give you a realistic sense of how markets behave, when and how technical analysis works, and what it really takes to trade successfully.

Statistics

Statistics
  • Author : Alan Agresti
  • Publisher :Unknown
  • Release Date :2013
  • Total pages :229
  • ISBN : 1269909290
GET BOOK HERE

Summary :

Transportation Systems Planning

Transportation Systems Planning
  • Author : Konstadinos G. Goulias
  • Publisher :Unknown
  • Release Date :2002-12-26
  • Total pages :456
  • ISBN : 9781420042283
GET BOOK HERE

Summary : Transportation engineering and transportation planning are two sides of the same coin aiming at the design of an efficient infrastructure and service to meet the growing needs for accessibility and mobility. Many well-designed transport systems that meet these needs are based on a solid understanding of human behavior. Since transportation systems are the backbone connecting the vital parts of a city, in-depth understanding of human nature is essential to the planning, design, and operational analysis of transportation systems. With contributions by transportation experts from around the world, Transportation Systems Planning: Methods and Applications compiles engineering data and methods for solving problems in the planning, design, construction, and operation of various transportation modes into one source. It is the first methodological transportation planning reference that illustrates analytical simulation methods that depict human behavior in a realistic way, and many of its chapters emphasize newly developed and previously unpublished simulation methods. The handbook demonstrates how urban and regional planning, geography, demography, economics, sociology, ecology, psychology, business, operations management, and engineering come together to help us plan for better futures that are human-centered. The text reviews projects from an initial problem statement to final policy action and associated decision-making and examines policies at all levels of government, from the city to the national levels. Unlike many other handbooks which are encyclopedic reviews, Transportation Systems Planning extends far beyond modeling in engineering and economics to present a truly transdisciplinary approach to transportation systems planning.

Fuzzing for Software Security Testing and Quality Assurance

Fuzzing for Software Security Testing and Quality Assurance
  • Author : Ari Takanen,Jared D. Demott,Charles Miller
  • Publisher :Unknown
  • Release Date :2008
  • Total pages :287
  • ISBN : 9781596932159
GET BOOK HERE

Summary : Learn the code cracker's malicious mindset, so you can find worn-size holes in the software you are designing, testing, and building. Fuzzing for Software Security Testing and Quality Assurance takes a weapon from the black-hat arsenal to give you a powerful new tool to build secure, high-quality software. This practical resource helps you add extra protection without adding expense or time to already tight schedules and budgets. The book shows you how to make fuzzing a standard practice that integrates seamlessly with all development activities. This comprehensive reference goes through each phase of software development and points out where testing and auditing can tighten security. It surveys all popular commercial fuzzing tools and explains how to select the right one for a software development project. The book also identifies those cases where commercial tools fall short and when there is a need for building your own fuzzing tools.

Analyzing the Analyzers

Analyzing the Analyzers
  • Author : Harlan Harris,Sean Murphy,Marck Vaisman
  • Publisher :Unknown
  • Release Date :2013-06-10
  • Total pages :40
  • ISBN : 9781449368401
GET BOOK HERE

Summary : 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

Applied Data Science

Applied Data Science
  • Author : Martin Braschler,Thilo Stadelmann,Kurt Stockinger
  • Publisher :Unknown
  • Release Date :2019-06-13
  • Total pages :465
  • ISBN : 9783030118211
GET BOOK HERE

Summary : This book has two main goals: to define data science through the work of data scientists and their results, namely data products, while simultaneously providing the reader with relevant lessons learned from applied data science projects at the intersection of academia and industry. As such, it is not a replacement for a classical textbook (i.e., it does not elaborate on fundamentals of methods and principles described elsewhere), but systematically highlights the connection between theory, on the one hand, and its application in specific use cases, on the other. With these goals in mind, the book is divided into three parts: Part I pays tribute to the interdisciplinary nature of data science and provides a common understanding of data science terminology for readers with different backgrounds. These six chapters are geared towards drawing a consistent picture of data science and were predominantly written by the editors themselves. Part II then broadens the spectrum by presenting views and insights from diverse authors – some from academia and some from industry, ranging from financial to health and from manufacturing to e-commerce. Each of these chapters describes a fundamental principle, method or tool in data science by analyzing specific use cases and drawing concrete conclusions from them. The case studies presented, and the methods and tools applied, represent the nuts and bolts of data science. Finally, Part III was again written from the perspective of the editors and summarizes the lessons learned that have been distilled from the case studies in Part II. The section can be viewed as a meta-study on data science across a broad range of domains, viewpoints and fields. Moreover, it provides answers to the question of what the mission-critical factors for success in different data science undertakings are. The book targets professionals as well as students of data science: first, practicing data scientists in industry and academia who want to broaden their scope and expand their knowledge by drawing on the authors’ combined experience. Second, decision makers in businesses who face the challenge of creating or implementing a data-driven strategy and who want to learn from success stories spanning a range of industries. Third, students of data science who want to understand both the theoretical and practical aspects of data science, vetted by real-world case studies at the intersection of academia and industry.

Data Mining with Rattle and R

Data Mining with Rattle and R
  • Author : Graham Williams
  • Publisher :Unknown
  • Release Date :2011-08-04
  • Total pages :374
  • ISBN : 9781441998903
GET BOOK HERE

Summary : Data mining is the art and science of intelligent data analysis. By building knowledge from information, data mining adds considerable value to the ever increasing stores of electronic data that abound today. In performing data mining many decisions need to be made regarding the choice of methodology, the choice of data, the choice of tools, and the choice of algorithms. Throughout this book the reader is introduced to the basic concepts and some of the more popular algorithms of data mining. With a focus on the hands-on end-to-end process for data mining, Williams guides the reader through various capabilities of the easy to use, free, and open source Rattle Data Mining Software built on the sophisticated R Statistical Software. The focus on doing data mining rather than just reading about data mining is refreshing. The book covers data understanding, data preparation, data refinement, model building, model evaluation, and practical deployment. The reader will learn to rapidly deliver a data mining project using software easily installed for free from the Internet. Coupling Rattle with R delivers a very sophisticated data mining environment with all the power, and more, of the many commercial offerings.

The Art of Data Analysis

The Art of Data Analysis
  • Author : Kristin H. Jarman
  • Publisher :Unknown
  • Release Date :2013-04-17
  • Total pages :190
  • ISBN : 9781118413340
GET BOOK HERE

Summary : A friendly and accessible approach to applying statistics in the real world With an emphasis on critical thinking, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics presents fun and unique examples, guides readers through the entire data collection and analysis process, and introduces basic statistical concepts along the way. Leaving proofs and complicated mathematics behind, the author portrays the more engaging side of statistics and emphasizes its role as a problem-solving tool. In addition, light-hearted case studies illustrate the application of statistics to real data analyses, highlighting the strengths and weaknesses of commonly used techniques. Written for the growing academic and industrial population that uses statistics in everyday life, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics highlights important issues that often arise when collecting and sifting through data. Featured concepts include: • Descriptive statistics • Analysis of variance • Probability and sample distributions • Confidence intervals • Hypothesis tests • Regression • Statistical correlation • Data collection • Statistical analysis with graphs Fun and inviting from beginning to end, The Art of Data Analysis is an ideal book for students as well as managers and researchers in industry, medicine, or government who face statistical questions and are in need of an intuitive understanding of basic statistical reasoning.

Analyzing Social Science Data

Analyzing Social Science Data
  • Author : David de Vaus
  • Publisher :Unknown
  • Release Date :2002-09-17
  • Total pages :401
  • ISBN : 0761959386
GET BOOK HERE

Summary : Abridged Contents PART ONE: HOW TO PREPARE DATA FOR ANALYSIS\PART TWO: HOW TO PREPARE VARIABLE FOR ANALYSIS\PART THREE: HOW TO REDUCE THE AMOUNT OF DATA TO ANALYZE\PART FOUR: HOW AND WHEN TO GENERALIZE\PART FIVE: HOW TO ANALYZE A SINGLE VARIABLE\PART SIX: HOW TO ANALYZE TWO VARIABLES\PART SEVEN: HOW TO CARRY OUT MULTIVARIATE ANALYSIS

The Art and Science of Learning from Data

The Art and Science of Learning from Data
  • Author : Alan Agresti,Chrstine A. Franklin,Bernhard Klingenberg
  • Publisher :Unknown
  • Release Date :2020
  • Total pages :229
  • ISBN : 0136468764
GET BOOK HERE

Summary : "One of our goals in writing this book was to help make the conceptual approach more interesting and more readily accessible to students. At the end of the course, we want students to look back at their statistics course and realize that they learned practical concepts that will serve them well for the rest of their lives. We also want students to come to appreciate that in practice, assumptions are not perfectly satisfied, models are not exactly correct, distributions are not exactly normally distributed, and different factors should be considered in conducting a statistical analysis. The title of our book reflects the experience of data analysts, who soon realize that statistics is an art as well as a science"--

Longitudinal Data Analysis

Longitudinal Data Analysis
  • Author : Jason Newsom,Richard N. Jones,Scott M. Hofer
  • Publisher :Unknown
  • Release Date :2012-05-22
  • Total pages :405
  • ISBN : 9781136705472
GET BOOK HERE

Summary : First Published in 2012. Routledge is an imprint of Taylor & Francis, an informa company.

Individual Differences in Sensory and Consumer Science

Individual Differences in Sensory and Consumer Science
  • Author : Tormod Næs,Paula Varela,Ingunn Berget
  • Publisher :Unknown
  • Release Date :2018-02-21
  • Total pages :260
  • ISBN : 9780081011140
GET BOOK HERE

Summary : Individual Differences in Sensory and Consumer Science: Experimentation, Analysis and Interpretation presents easily readable, state-of-the-art coverage on how to plan and execute experiments that give rise to individual differences, also providing the framework for successful analysis and interpretation of results. The book highlights the different methodologies that can be applied and how to select the correct methodology based on the type of study you are performing, be it product research and development, quality control or consumer acceptance studies. Written by an experienced team of statisticians and sensory and consumer scientists, the book provides both academics and industry professionals with the first complete overview of a topic of ever-increasing importance. Identifies how to plan and execute experiments in sensory and consumer science Analyzes and interprets individual variances in sensory and consumer research Differentiates best practices for examining product development, quality control and consumer acceptance

Computer Security

Computer Security
  • Author : Matt Bishop
  • Publisher :Unknown
  • Release Date :2003
  • Total pages :1084
  • ISBN : 0201440997
GET BOOK HERE

Summary : The importance of computer security has increased dramatically during the past few years. Bishop provides a monumental reference for the theory and practice of computer security. Comprehensive in scope, this book covers applied and practical elements, theory, and the reasons for the design of applications and security techniques.

Managing Data Science

Managing Data Science
  • Author : Kirill Dubovikov
  • Publisher :Unknown
  • Release Date :2019-11-12
  • Total pages :290
  • ISBN : 9781838824563
GET BOOK HERE

Summary : Understand data science concepts and methodologies to manage and deliver top-notch solutions for your organization Key Features Learn the basics of data science and explore its possibilities and limitations Manage data science projects and assemble teams effectively even in the most challenging situations Understand management principles and approaches for data science projects to streamline the innovation process Book Description Data science and machine learning can transform any organization and unlock new opportunities. However, employing the right management strategies is crucial to guide the solution from prototype to production. Traditional approaches often fail as they don't entirely meet the conditions and requirements necessary for current data science projects. In this book, you'll explore the right approach to data science project management, along with useful tips and best practices to guide you along the way. After understanding the practical applications of data science and artificial intelligence, you'll see how to incorporate them into your solutions. Next, you will go through the data science project life cycle, explore the common pitfalls encountered at each step, and learn how to avoid them. Any data science project requires a skilled team, and this book will offer the right advice for hiring and growing a data science team for your organization. Later, you'll be shown how to efficiently manage and improve your data science projects through the use of DevOps and ModelOps. By the end of this book, you will be well versed with various data science solutions and have gained practical insights into tackling the different challenges that you'll encounter on a daily basis. What you will learn Understand the underlying problems of building a strong data science pipeline Explore the different tools for building and deploying data science solutions Hire, grow, and sustain a data science team Manage data science projects through all stages, from prototype to production Learn how to use ModelOps to improve your data science pipelines Get up to speed with the model testing techniques used in both development and production stages Who this book is for This book is for data scientists, analysts, and program managers who want to use data science for business productivity by incorporating data science workflows efficiently. Some understanding of basic data science concepts will be useful to get the most out of this book.

The Art of Data Science

The Art of Data Science
  • Author : Roger D. Peng,Elizabeth Matsui
  • Publisher :Unknown
  • Release Date :2016-06-08
  • Total pages :170
  • ISBN : 1365061469
GET BOOK HERE

Summary : "This book describes the process of analyzing data. The authors have extensive experience both managing data analysts and conducting their own data analyses, and this book is a distillation of their experience in a format that is applicable to both practitioners and managers in data science."--Leanpub.com.

Introduction to Data Science

Introduction to Data Science
  • Author : Rafael A. Irizarry
  • Publisher :Unknown
  • Release Date :2019-11-20
  • Total pages :713
  • ISBN : 9781000708035
GET BOOK HERE

Summary : Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.