Introduction to Data Processing PDF Download

Author: Robert R. Arnold
Publisher:
ISBN:
Category : Business
Languages : en
Pages : 350

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Book Description

Author: Gary S. Popkin
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 488

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Book Description

Author: Beryl Robichaud
Publisher: Gregg Division McGraw-Hill
ISBN:
Category : Business & Economics
Languages : en
Pages : 360

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Book Description
Introduces the Nontechnical User to Computers & Programming in BASIC. Supplies Information on Computer-Related Career Opportunities

Author: Gary B. Shelly
Publisher: Brooks/Cole
ISBN:
Category : Computers
Languages : en
Pages : 516

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Book Description

Author: Robert R. Arnold
Publisher:
ISBN:
Category : Business
Languages : en
Pages : 344

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Book Description

Author: Susan Wooldridge
Publisher: Elsevier
ISBN: 1483105245
Category : Technology & Engineering
Languages : en
Pages : 256

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Book Description
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: Lawrence Orilia
Publisher: McGraw-Hill Companies
ISBN:
Category : Business
Languages : en
Pages : 776

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Book Description
Introduces Computers & Business Data Processing in a Nontechnical Form. Covers Subjects from Flowcharting & Languages to Computerized Crime & Word Processing

Author: Margaret Schlosser Wu
Publisher: Houghton Mifflin Harcourt P
ISBN:
Category : Computers
Languages : en
Pages : 542

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Book Description

Author: Guy Lebanon
Publisher: Springer
ISBN: 3319981498
Category : Computers
Languages : en
Pages : 576

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Book Description
This book introduces basic computing skills designed for industry professionals without a strong computer science background. Written in an easily accessible manner, and accompanied by a user-friendly website, it serves as a self-study guide to survey data science and data engineering for those who aspire to start a computing career, or expand on their current roles, in areas such as applied statistics, big data, machine learning, data mining, and informatics. The authors draw from their combined experience working at software and social network companies, on big data products at several major online retailers, as well as their experience building big data systems for an AI startup. Spanning from the basic inner workings of a computer to advanced data manipulation techniques, this book opens doors for readers to quickly explore and enhance their computing knowledge. Computing with Data comprises a wide range of computational topics essential for data scientists, analysts, and engineers, providing them with the necessary tools to be successful in any role that involves computing with data. The introduction is self-contained, and chapters progress from basic hardware concepts to operating systems, programming languages, graphing and processing data, testing and programming tools, big data frameworks, and cloud computing. The book is fashioned with several audiences in mind. Readers without a strong educational background in CS--or those who need a refresher--will find the chapters on hardware, operating systems, and programming languages particularly useful. Readers with a strong educational background in CS, but without significant industry background, will find the following chapters especially beneficial: learning R, testing, programming, visualizing and processing data in Python and R, system design for big data, data stores, and software craftsmanship.

Author: Rafael A. Irizarry
Publisher: CRC Press
ISBN: 1000708039
Category : Mathematics
Languages : en
Pages : 794

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Book Description
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.