Book picks similar to
Simulation Modeling & Analysis by Averill M. Law
simulation
engineering
statistics
technical
Data Modeling Essentials
Graeme Simsion - 1992
In order to enable students to apply the basics of data modeling to real models, the book addresses the realities of developing systems in real-world situations by assessing the merits of a variety of possible solutions as well as using language and diagramming methods that represent industry practice.This revised edition has been given significantly expanded coverage and reorganized for greater reader comprehension even as it retains its distinctive hallmarks of readability and usefulness. Beginning with the basics, the book provides a thorough grounding in theory before guiding the reader through the various stages of applied data modeling and database design. Later chapters address advanced subjects, including business rules, data warehousing, enterprise-wide modeling and data management. It includes an entirely new section discussing the development of logical and physical modeling, along with new material describing a powerful technique for model verification. It also provides an excellent resource for additional lectures and exercises.This text is the ideal reference for data modelers, data architects, database designers, DBAs, and systems analysts, as well as undergraduate and graduate-level students looking for a real-world perspective.
Systems Analysis and Design
Alan Dennis - 2002
Building on their experience as professional systems analysts and award-winning teachers, authors Dennis, Wixom, and Roth capture the experience of developing and analyzing systems in a way that students can understand and apply.With
Systems Analysis and Design, 4th edition
, students will leave the course with experience that is a rich foundation for further work as a systems analyst.
Spreadsheet Modeling & Decision Analysis: A Practical Introduction to Management Science
Cliff T. Ragsdale - 1997
. . everything you need to master the most widely used management science techniques using Microsoft Excel is right here Learning to make decisions in today's business world takes training and experience. Cliff Ragsdale--the respected innovator in the field of management science--is an outstanding guide to help you learn the skills you need, use Microsoft Excel for Windows to implement those skills, and gain the confidence to apply what you learn to real business situations. SPREADSHEET MODELING AND DECISION ANALYSIS gives you step-by-step instructions and annotated screen shots to make examples easy to follow. Plus, interesting sections called The World of Management Science show you how each topic has been applied in a real company.
Programming PHP
Rasmus Lerdorf - 2000
When it comes to creating websites, the PHP scripting language is truly a red-hot property. In fact, PHP is currently used on more than 19 million websites, surpassing Microsoft's ASP .NET technology in popularity. Programmers love its flexibility and speed; designers love its accessibility and convenience. As the industry standard book on PHP, all of the essentials are covered in a clear and concise manner. Language syntax and programming techniques are coupled with numerous examples that illustrate both correct usage and common idioms. With style tips and practical programming advice, this book will help you become not just a PHP programmer, but a good PHP programmer. Programming PHP, Second Edition covers everything you need to know to create effective web applications with PHP. Contents include: Detailed information on the basics of the PHP language, including data types, variables, operators, and flow control statements Chapters outlining the basics of functions, strings, arrays, and objects Coverage of common PHP web application techniques, such as form processing and validation, session tracking, and cookies Material on interacting with relational databases, such as MySQL and Oracle, using the database-independent PEAR DB library and the new PDO Library Chapters that show you how to generate dynamic images, create PDF files, and parse XML files with PHP Advanced topics, such as creating secure scripts, error handling, performance tuning, and writing your own C language extensions to PHP A handy quick reference to all the core functions in PHP and all the standard extensions that ship with PHP Praise for the first edition: "If you are just getting into the dynamic Web development world or you are considering migrating from another dynamic web product to PHP, Programming PHP is the book of choice to get you up, running, and productive in a short time."--Peter MacIntrye, eWeek "I think this is a great book for programmers who want to start developing dynamic websites with PHP. It gives a detailed overview of PHP, lots of valuable tips, and a good sense of PHP's strengths."--David Dooling, Slashdot.org
Text Mining with R: A Tidy Approach
Julia Silge - 2017
With this practical book, you'll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like ggraph and dplyr. You'll learn how tidytext and other tidy tools in R can make text analysis easier and more effective.The authors demonstrate how treating text as data frames enables you to manipulate, summarize, and visualize characteristics of text. You'll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature, news, and social media.Learn how to apply the tidy text format to NLPUse sentiment analysis to mine the emotional content of textIdentify a document's most important terms with frequency measurementsExplore relationships and connections between words with the ggraph and widyr packagesConvert back and forth between R's tidy and non-tidy text formatsUse topic modeling to classify document collections into natural groupsExamine case studies that compare Twitter archives, dig into NASA metadata, and analyze thousands of Usenet messages
Computer Vision: Algorithms and Applications
Richard Szeliski - 2010
However, despite all of the recent advances in computer vision research, the dream of having a computer interpret an image at the same level as a two-year old remains elusive. Why is computer vision such a challenging problem and what is the current state of the art?Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos.More than just a source of "recipes," this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniquesTopics and features: Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses Presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects Provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory Suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book Supplies supplementary course material for students at the associated website, http: //szeliski.org/Book/ Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.
The Art of Electronics
Paul Horowitz - 1980
Widely accepted as the authoritative text and reference on electronic circuit design, both analog and digital, this book revolutionized the teaching of electronics by emphasizing the methods actually used by circuit designers -- a combination of some basic laws, rules of thumb, and a large bag of tricks. The result is a largely nonmathematical treatment that encourages circuit intuition, brainstorming, and simplified calculations of circuit values and performance. The new Art of Electronics retains the feeling of informality and easy access that helped make the first edition so successful and popular. It is an ideal first textbook on electronics for scientists and engineers and an indispensable reference for anyone, professional or amateur, who works with electronic circuits.
The Unified Software Development Process
Ivar Jacobson - 1999
This book demonstrates how the notation and process complement one another, using UML models to illustrate the new process in action. It describes the constructs such as use cases, actors, and more.
Microwave Engineering
David M. Pozar - 1990
The author successfully introduces Maxwell's equations, wave propagation, network analysis, and design principles as applied to modern microwave engineering. A considerable amount of material in this book is related to the design of specific microwave circuits and components, for both practical and motivational value. It also presents the analysis and logic behind these designs so that the reader can see and understand the process of applying the fundamental concepts to arrive at useful results. The derivations are well laid out and the majority of each chapter's formulas are displayed in a nice tabular format every few pages. This Third Edition offers greatly expanded coverage with new material on: Noise; Nonlinear effects; RF MEMs; transistor power amplifiers; FET mixers; oscillator phase noise; transistor oscillators and frequency multiplier.
Statistics Without Tears: An Introduction for Non-Mathematicians
Derek Rowntree - 1981
With it you can prime yourself with the key concepts of statistics before getting involved in the associated calculations. Using words and diagrams instead of figures, formulae and equations, Derek Rowntree makes statistics accessible to those who are non-mathematicians. And just to get you into the spirit of things. Rowntree has included questions in his argument; answer them as you go and you will be able to tell how far you have mastered the subject.
Data Smart: Using Data Science to Transform Information into Insight
John W. Foreman - 2013
Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.
Hacker's Delight
Henry S. Warren Jr. - 2002
Aiming to tell the dark secrets of computer arithmetic, this title is suitable for library developers, compiler writers, and lovers of elegant hacks.
Pmp Exam Prep: Rita's Course in a Book for Passing the Pmp Exam
Rita Mulcahy - 1999
Is it Rita's years of PMP exam preparation experience? The endless hours of ongoing research? The interviews with project managers who failed the exam, to identify gaps in their knowledge? Or is it the razor-sharp focus on making sure project managers don't waste a single minute of their time studying any more than they absolutely have to? Actually, it's all of the above. PMP Exam Prep, Sixth Edition by Rita Mulcahy contains hundreds of updates and improvements from previous editions--including new exercises and sample questions never before in print. Offering hundreds of sample questions, critical time-saving tips plus games and activities available nowhere else, this book will help you pass the PMP exam on your first try.
Organic Chemistry I for Dummies
Arthur Winter - 2005
This book is an easy-to-understand and fun reference to this challenging subject. It explains the principles of organic chemistry in simple terms and includes worked-out problems to help readers get up to speed on the basics.
Introductory Statistics
Neil A. Weiss - 1987
This book develops statistical thinking over rote drill and practice. The Nature of Statistics; Organizing Data; Descriptive Measures; Probability Concepts; Discrete Random Variables; The Normal Distribution; The Sampling Distribution of the Sample Menu; Confidence Intervals for One Population Mean; Hypothesis Tests for One Population Mean; Inferences for Two Population Means; Inferences for Population Standard Deviations; Inferences for Population Proportions; Chi-Square Procedures; Descriptive Methods in Regression and Correlation; Inferential Methods in Regression and Correlation; Analysis of Variance (ANOVA)
For all readers interested in Introductory Statistics.