New Perspectives on Computer Concepts 2018: Introductory PDF Download
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Author: June Jamrich Parsons
Publisher: Cengage Learning
ISBN: 9781305951518
Category : Computers
Languages : en
Pages : 632
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Book Description
In today’s world where technology impacts every aspect of life, you need to know how to evaluate devices, choose apps, maintain a professional online reputation, and ensure digital security. NEW PERSPECTIVES ON COMPUTER CONCEPTS 2018, INTRODUCTORY offers the insights to help. This book goes beyond the intuitive how-to of apps and social media to delve into broad concepts that are guiding current technologies such as self-driving cars, virtual reality, file sharing torrents, encrypted communications, photo forensics, and the Internet of Things. Numerous illustrations and interactive features make mastering technical topics a breeze, while the book’s proven learning path is structured with today's busy reader in mind. This edition offers an insightful overview of what today’s readers must know about using technology to complete an education, secure a successful career, and engage in issues that shape today's world. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Author: June Jamrich Parsons
Publisher: Cengage Learning
ISBN: 9781305951518
Category : Computers
Languages : en
Pages : 632
Get Book Here
Book Description
In today’s world where technology impacts every aspect of life, you need to know how to evaluate devices, choose apps, maintain a professional online reputation, and ensure digital security. NEW PERSPECTIVES ON COMPUTER CONCEPTS 2018, INTRODUCTORY offers the insights to help. This book goes beyond the intuitive how-to of apps and social media to delve into broad concepts that are guiding current technologies such as self-driving cars, virtual reality, file sharing torrents, encrypted communications, photo forensics, and the Internet of Things. Numerous illustrations and interactive features make mastering technical topics a breeze, while the book’s proven learning path is structured with today's busy reader in mind. This edition offers an insightful overview of what today’s readers must know about using technology to complete an education, secure a successful career, and engage in issues that shape today's world. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Author: Jon Stokes
Publisher: No Starch Press
ISBN: 1593271042
Category : Computers
Languages : en
Pages : 320
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Book Description
Om hvordan mikroprocessorer fungerer, med undersøgelse af de nyeste mikroprocessorer fra Intel, IBM og Motorola.
Author: Nat Gertler
Publisher: Prentice Hall
ISBN:
Category : Computers
Languages : en
Pages : 260
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Book Description
A visually oriented conceptual guide to understanding how a computer works. Using a strongly visual format similar to that of popular magazines or modern multi-media presentations, this book shows the reader how each PC subsystem is constructed, how it works, and how it relates to other PC subsystems.
Author: June Jamrich Parsons
Publisher:
ISBN: 9780760061442
Category : Computers
Languages : en
Pages : 380
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Book Description
Master concepts quickly and easily with the Illustrated Series form Course Technology--the quick, visual way to learn about cutting-edge computer concepts!
Author: Ian Goodfellow
Publisher: MIT Press
ISBN: 0262337371
Category : Computers
Languages : en
Pages : 801
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Book Description
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Author: Steven A. Frank
Publisher: Springer
ISBN: 3319917072
Category : Technology & Engineering
Languages : en
Pages : 112
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Book Description
This open access Brief introduces the basic principles of control theory in a concise self-study guide. It complements the classic texts by emphasizing the simple conceptual unity of the subject. A novice can quickly see how and why the different parts fit together. The concepts build slowly and naturally one after another, until the reader soon has a view of the whole. Each concept is illustrated by detailed examples and graphics. The full software code for each example is available, providing the basis for experimenting with various assumptions, learning how to write programs for control analysis, and setting the stage for future research projects. The topics focus on robustness, design trade-offs, and optimality. Most of the book develops classical linear theory. The last part of the book considers robustness with respect to nonlinearity and explicitly nonlinear extensions, as well as advanced topics such as adaptive control and model predictive control. New students, as well as scientists from other backgrounds who want a concise and easy-to-grasp coverage of control theory, will benefit from the emphasis on concepts and broad understanding of the various approaches. Electronic codes for this title can be downloaded from https://extras.springer.com/?query=978-3-319-91707-8
Author: Thomas Erl
Publisher: Pearson Education
ISBN: 0133387526
Category : Business & Economics
Languages : en
Pages : 533
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Book Description
This book describes cloud computing as a service that is "highly scalable" and operates in "a resilient environment". The authors emphasize architectural layers and models - but also business and security factors.
Author: Chase Roberts
Publisher:
ISBN: 9781735208701
Category :
Languages : en
Pages : 0
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Book Description
An introduction to computer engineering for babies. Learn basic logic gates with hands on examples of buttons and an output LED.
Author: David Evans
Publisher:
ISBN: 9780983455752
Category :
Languages : en
Pages : 300
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Book Description
Introduction to Computing is a comprehensive text designed for the CS0 (Intro to CS) course at the college level. It may also be used as a primary text for the Advanced Placement Computer Science course at the high school level.
Author: Oscar Levin
Publisher: Createspace Independent Publishing Platform
ISBN: 9781534970748
Category :
Languages : en
Pages : 342
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Book Description
This gentle introduction to discrete mathematics is written for first and second year math majors, especially those who intend to teach. The text began as a set of lecture notes for the discrete mathematics course at the University of Northern Colorado. This course serves both as an introduction to topics in discrete math and as the "introduction to proof" course for math majors. The course is usually taught with a large amount of student inquiry, and this text is written to help facilitate this. Four main topics are covered: counting, sequences, logic, and graph theory. Along the way proofs are introduced, including proofs by contradiction, proofs by induction, and combinatorial proofs. The book contains over 360 exercises, including 230 with solutions and 130 more involved problems suitable for homework. There are also Investigate! activities throughout the text to support active, inquiry based learning. While there are many fine discrete math textbooks available, this text has the following advantages: It is written to be used in an inquiry rich course. It is written to be used in a course for future math teachers. It is open source, with low cost print editions and free electronic editions.
