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Author : Gary B. Shelly
Publisher : Brooks/Cole
ISBN 13 :
Total Pages : 516 pages
Book Rating : 4.:/5 (319 download)
Download or read book Introduction to Computers and Data Processing written by Gary B. Shelly and published by Brooks/Cole. This book was released on 1980 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Alberta Authorized Resource for grade 10-12 ca 1980-1997.
Author : Rafael A. Irizarry
Publisher : CRC Press
ISBN 13 : 1000708039
Total Pages : 836 pages
Book Rating : 4.0/5 (7 download)
Download or read book Introduction to Data Science written by Rafael A. Irizarry and published by CRC Press. This book was released on 2019-11-20 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Susan Wooldridge
Publisher : Elsevier
ISBN 13 : 1483105245
Total Pages : 272 pages
Book Rating : 4.4/5 (831 download)
Download or read book Data Processing written by Susan Wooldridge and published by Elsevier. This book was released on 2013-10-22 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Processing: Made Simple, Second Edition presents discussions of a number of trends and developments in the world of commercial data processing. The book covers the rapid growth of micro- and mini-computers for both home and office use; word processing and the 'automated office'; the advent of distributed data processing; and the continued growth of database-oriented systems. The text also discusses modern digital computers; fundamental computer concepts; information and data processing requirements of commercial organizations; and the historical perspective of the computer industry. The computer hardware and software and the development and implementation of a computer system are considered. The book tackles careers in data processing; the tasks carried out by the data processing department; and the way in which the data processing department fits in with the rest of the organization. The text concludes by examining some of the problems of running a data processing department, and by suggesting some possible solutions. Computer science students will find the book invaluable.
Author : Hadley Wickham
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491910364
Total Pages : 521 pages
Book Rating : 4.4/5 (919 download)
Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Author : João Moreira
Publisher : John Wiley & Sons
ISBN 13 : 1119296242
Total Pages : 352 pages
Book Rating : 4.1/5 (192 download)
Download or read book A General Introduction to Data Analytics written by João Moreira and published by John Wiley & Sons. This book was released on 2018-07-18 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming A General Introduction to Data Analytics is an essential guide to understand and use data analytics. This book is written using easy-to-understand terms and does not require familiarity with statistics or programming. The authors—noted experts in the field—highlight an explanation of the intuition behind the basic data analytics techniques. The text also contains exercises and illustrative examples. Thought to be easily accessible to non-experts, the book provides motivation to the necessity of analyzing data. It explains how to visualize and summarize data, and how to find natural groups and frequent patterns in a dataset. The book also explores predictive tasks, be them classification or regression. Finally, the book discusses popular data analytic applications, like mining the web, information retrieval, social network analysis, working with text, and recommender systems. The learning resources offer: A guide to the reasoning behind data mining techniques A unique illustrative example that extends throughout all the chapters Exercises at the end of each chapter and larger projects at the end of each of the text’s two main parts Together with these learning resources, the book can be used in a 13-week course guide, one chapter per course topic. The book was written in a format that allows the understanding of the main data analytics concepts by non-mathematicians, non-statisticians and non-computer scientists interested in getting an introduction to data science. A General Introduction to Data Analytics is a basic guide to data analytics written in highly accessible terms.
Author : Laura Igual
Publisher : Springer
ISBN 13 : 3319500171
Total Pages : 227 pages
Book Rating : 4.3/5 (195 download)
Download or read book Introduction to Data Science written by Laura Igual and published by Springer. This book was released on 2017-02-22 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.
Author : Renee M. P. Teate
Publisher : John Wiley & Sons
ISBN 13 : 1119669391
Total Pages : 400 pages
Book Rating : 4.1/5 (196 download)
Download or read book SQL for Data Scientists written by Renee M. P. Teate and published by John Wiley & Sons. This book was released on 2021-08-17 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Jump-start your career as a data scientist—learn to develop datasets for exploration, analysis, and machine learning SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that’s dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls. You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data. This guide for data scientists differs from other instructional guides on the subject. It doesn’t cover SQL broadly. Instead, you’ll learn the subset of SQL skills that data analysts and data scientists use frequently. You’ll also gain practical advice and direction on "how to think about constructing your dataset." Gain an understanding of relational database structure, query design, and SQL syntax Develop queries to construct datasets for use in applications like interactive reports and machine learning algorithms Review strategies and approaches so you can design analytical datasets Practice your techniques with the provided database and SQL code In this book, author Renee Teate shares knowledge gained during a 15-year career working with data, in roles ranging from database developer to data analyst to data scientist. She guides you through SQL code and dataset design concepts from an industry practitioner’s perspective, moving your data scientist career forward!
Author : Melissa A Hardy
Publisher : SAGE
ISBN 13 : 1446203441
Total Pages : 729 pages
Book Rating : 4.4/5 (462 download)
Download or read book Handbook of Data Analysis written by Melissa A Hardy and published by SAGE. This book was released on 2009-06-17 with total page 729 pages. Available in PDF, EPUB and Kindle. Book excerpt: ′This book provides an excellent reference guide to basic theoretical arguments, practical quantitative techniques and the methodologies that the majority of social science researchers are likely to require for postgraduate study and beyond′ - Environment and Planning ′The book provides researchers with guidance in, and examples of, both quantitative and qualitative modes of analysis, written by leading practitioners in the field. The editors give a persuasive account of the commonalities of purpose that exist across both modes, as well as demonstrating a keen awareness of the different things that each offers the practising researcher′ - Clive Seale, Brunel University ′With the appearance of this handbook, data analysts no longer have to consult dozens of disparate publications to carry out their work. The essential tools for an intelligent telling of the data story are offered here, in thirty chapters written by recognized experts. ′ - Michael Lewis-Beck, F Wendell Miller Distinguished Professor of Political Science, University of Iowa ′This is an excellent guide to current issues in the analysis of social science data. I recommend it to anyone who is looking for authoritative introductions to the state of the art. Each chapter offers a comprehensive review and an extensive bibliography and will be invaluable to researchers wanting to update themselves about modern developments′ - Professor Nigel Gilbert, Pro Vice-Chancellor and Professor of Sociology, University of Surrey This is a book that will rapidly be recognized as the bible for social researchers. It provides a first-class, reliable guide to the basic issues in data analysis, such as the construction of variables, the characterization of distributions and the notions of inference. Scholars and students can turn to it for teaching and applied needs with confidence. The book also seeks to enhance debate in the field by tackling more advanced topics such as models of change, causality, panel models and network analysis. Specialists will find much food for thought in these chapters. A distinctive feature of the book is the breadth of coverage. No other book provides a better one-stop survey of the field of data analysis. In 30 specially commissioned chapters the editors aim to encourage readers to develop an appreciation of the range of analytic options available, so they can choose a research problem and then develop a suitable approach to data analysis.
Author : Kristin H. Jarman
Publisher : John Wiley & Sons
ISBN 13 : 1118411315
Total Pages : 192 pages
Book Rating : 4.1/5 (184 download)
Download or read book The Art of Data Analysis written by Kristin H. Jarman and published by John Wiley & Sons. This book was released on 2013-05-13 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Alfonso Zamora Saiz
Publisher : Springer Nature
ISBN 13 : 3030489973
Total Pages : 289 pages
Book Rating : 4.0/5 (34 download)
Download or read book An Introduction to Data Analysis in R written by Alfonso Zamora Saiz and published by Springer Nature. This book was released on 2020-07-27 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook offers an easy-to-follow, practical guide to modern data analysis using the programming language R. The chapters cover topics such as the fundamentals of programming in R, data collection and preprocessing, including web scraping, data visualization, and statistical methods, including multivariate analysis, and feature exercises at the end of each section. The text requires only basic statistics skills, as it strikes a balance between statistical and mathematical understanding and implementation in R, with a special emphasis on reproducible examples and real-world applications. This textbook is primarily intended for undergraduate students of mathematics, statistics, physics, economics, finance and business who are pursuing a career in data analytics. It will be equally valuable for master students of data science and industry professionals who want to conduct data analyses.
Author : Tiffany Bergin
Publisher : SAGE
ISBN 13 : 1526452316
Total Pages : 363 pages
Book Rating : 4.5/5 (264 download)
Download or read book An Introduction to Data Analysis written by Tiffany Bergin and published by SAGE. This book was released on 2018-10-15 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covering the general process of data analysis to finding, collecting, organizing, and presenting data, this book offers a complete introduction to the fundamentals of data analysis. Using real-world case studies as illustrations, it helps readers understand theories behind and develop techniques for conducting quantitative, qualitative, and mixed methods data analysis. With an easy-to-follow organization and clear, jargon-free language, it helps readers not only become proficient data analysts, but also develop the critical thinking skills necessary to assess analyses presented by others in both academic research and the popular media. It includes advice on: - Data analysis frameworks - Validity and credibility of data - Sampling techniques - Data management - The big data phenomenon - Data visualisation - Effective data communication Whether you are new to data analysis or looking for a quick-reference guide to key principles of the process, this book will help you uncover nuances, complexities, patterns, and relationships among all types of data.
Author : Davy Cielen
Publisher : Simon and Schuster
ISBN 13 : 1638352496
Total Pages : 475 pages
Book Rating : 4.6/5 (383 download)
Download or read book Introducing Data Science written by Davy Cielen and published by Simon and Schuster. This book was released on 2016-05-02 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Introducing Data Science teaches you how to accomplish the fundamental tasks that occupy data scientists. Using the Python language and common Python libraries, you'll experience firsthand the challenges of dealing with data at scale and gain a solid foundation in data science. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Many companies need developers with data science skills to work on projects ranging from social media marketing to machine learning. Discovering what you need to learn to begin a career as a data scientist can seem bewildering. This book is designed to help you get started. About the Book Introducing Data ScienceIntroducing Data Science explains vital data science concepts and teaches you how to accomplish the fundamental tasks that occupy data scientists. You’ll explore data visualization, graph databases, the use of NoSQL, and the data science process. You’ll use the Python language and common Python libraries as you experience firsthand the challenges of dealing with data at scale. Discover how Python allows you to gain insights from data sets so big that they need to be stored on multiple machines, or from data moving so quickly that no single machine can handle it. This book gives you hands-on experience with the most popular Python data science libraries, Scikit-learn and StatsModels. After reading this book, you’ll have the solid foundation you need to start a career in data science. What’s Inside Handling large data Introduction to machine learning Using Python to work with data Writing data science algorithms About the Reader This book assumes you're comfortable reading code in Python or a similar language, such as C, Ruby, or JavaScript. No prior experience with data science is required. About the Authors Davy Cielen, Arno D. B. Meysman, and Mohamed Ali are the founders and managing partners of Optimately and Maiton, where they focus on developing data science projects and solutions in various sectors. Table of Contents Data science in a big data world The data science process Machine learning Handling large data on a single computer First steps in big data Join the NoSQL movement The rise of graph databases Text mining and text analytics Data visualization to the end user
Author : United States. Congress. House. Committee on Government Operations. Government Activities Subcommittee
Publisher :
ISBN 13 :
Total Pages : 452 pages
Book Rating : 4.0/5 (12 download)
Download or read book Data Processing Management in the Federal Government written by United States. Congress. House. Committee on Government Operations. Government Activities Subcommittee and published by . This book was released on 1967 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: Examines Bureau of Budget, GSA, and National Bureau of Standards electronic data processing systems management programs. Appendix includes report of the President's Science Advisory Committee "Computers in Higher Education" (Feb. 1967, p. 255-337).
Author : Paul Murrell
Publisher : CRC Press
ISBN 13 : 1420065181
Total Pages : 445 pages
Book Rating : 4.4/5 (2 download)
Download or read book Introduction to Data Technologies written by Paul Murrell and published by CRC Press. This book was released on 2009-02-23 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing key information on how to work with research data, Introduction to Data Technologies presents ideas and techniques for performing critical, behind-the-scenes tasks that take up so much time and effort yet typically receive little attention in formal education. With a focus on computational tools, the book shows readers how to improve thei
Author : Srini Penchikala
Publisher : Lulu.com
ISBN 13 : 1387659952
Total Pages : 106 pages
Book Rating : 4.3/5 (876 download)
Download or read book Big Data Processing with Apache Spark written by Srini Penchikala and published by Lulu.com. This book was released on 2018-03-13 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: Apache Spark is a popular open-source big-data processing framework thatÕs built around speed, ease of use, and unified distributed computing architecture. Not only it supports developing applications in different languages like Java, Scala, Python, and R, itÕs also hundred times faster in memory and ten times faster even when running on disk compared to traditional data processing frameworks. Whether you are currently working on a big data project or interested in learning more about topics like machine learning, streaming data processing, and graph data analytics, this book is for you. You can learn about Apache Spark and develop Spark programs for various use cases in big data analytics using the code examples provided. This book covers all the libraries in Spark ecosystem: Spark Core, Spark SQL, Spark Streaming, Spark ML, and Spark GraphX.
Author : John V. Guttag
Publisher : MIT Press
ISBN 13 : 0262529629
Total Pages : 466 pages
Book Rating : 4.2/5 (625 download)
Download or read book Introduction to Computation and Programming Using Python, second edition written by John V. Guttag and published by MIT Press. This book was released on 2016-08-12 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.
Author : Hector Cuesta
Publisher : Packt Publishing Ltd
ISBN 13 : 1785286668
Total Pages : 330 pages
Book Rating : 4.7/5 (852 download)
Download or read book Practical Data Analysis written by Hector Cuesta and published by Packt Publishing Ltd. This book was released on 2016-09-30 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache Spark About This Book Learn to use various data analysis tools and algorithms to classify, cluster, visualize, simulate, and forecast your data Apply Machine Learning algorithms to different kinds of data such as social networks, time series, and images A hands-on guide to understanding the nature of data and how to turn it into insight Who This Book Is For This book is for developers who want to implement data analysis and data-driven algorithms in a practical way. It is also suitable for those without a background in data analysis or data processing. Basic knowledge of Python programming, statistics, and linear algebra is assumed. What You Will Learn Acquire, format, and visualize your data Build an image-similarity search engine Generate meaningful visualizations anyone can understand Get started with analyzing social network graphs Find out how to implement sentiment text analysis Install data analysis tools such as Pandas, MongoDB, and Apache Spark Get to grips with Apache Spark Implement machine learning algorithms such as classification or forecasting In Detail Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you'll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark. Style and approach This is a hands-on guide to data analysis and data processing. The concrete examples are explained with simple code and accessible data.
