- Table View
- List View
Statistik-Workshop für Programmierer
by Allen B. DowneyWenn Sie programmieren können, beherrschen Sie bereits Techniken, um aus Daten Wissen zu extrahieren. Diese kompakte Einführung in die Statistik zeigt Ihnen, wie Sie rechnergestützt, anstatt auf mathematischem Weg Datenanalysen mit Python durchführen können. Praktischer Programmier-Workshop statt grauer Theorie: Das Buch führt Sie anhand eines durchgängigen Fallbeispiels durch eine vollständige Datenanalyse -- von der Datensammlung über die Berechnung statistischer Kennwerte und Identifikation von Mustern bis hin zum Testen statistischer Hypothesen. Gleichzeitig werden Sie mit statistischen Verteilungen, den Regeln der Wahrscheinlichkeitsrechnung, Visualisierungsmöglichkeiten und vielen anderen Arbeitstechniken und Konzepten vertraut gemacht. Statistik-Konzepte zum Ausprobieren: Entwickeln Sie über das Schreiben und Testen von Code ein Verständnis für die Grundlagen von Wahrscheinlichkeitsrechnung und Statistik: Überprüfen Sie das Verhalten statistischer Merkmale durch Zufallsexperimente, zum Beispiel indem Sie Stichproben aus unterschiedlichen Verteilungen ziehen. Nutzen Sie Simulationen, um Konzepte zu verstehen, die auf mathematischem Weg nur schwer zugänglich sind. Lernen Sie etwas über Themen, die in Einführungen üblicherweise nicht vermittelt werden, beispielsweise über die Bayessche Schätzung. Nutzen Sie Python zur Bereinigung und Aufbereitung von Rohdaten aus nahezu beliebigen Quellen. Beantworten Sie mit den Mitteln der Inferenzstatistik Fragestellungen zu realen Daten.
Think Bayes
by Allen B. DowneyIf you know how to program with Python and also know a little about probability, you're ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical notation, and use discrete probability distributions instead of continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer, and you'll begin to apply these techniques to real-world problems.Bayesian statistical methods are becoming more common and more important, but not many resources are available to help beginners. Based on undergraduate classes taught by author Allen Downey, this book's computational approach helps you get a solid start.Use your existing programming skills to learn and understand Bayesian statisticsWork with problems involving estimation, prediction, decision analysis, evidence, and hypothesis testingGet started with simple examples, using coins, M&Ms, Dungeons & Dragons dice, paintball, and hockeyLearn computational methods for solving real-world problems, such as interpreting SAT scores, simulating kidney tumors, and modeling the human microbiome.<P><P> Advisory: Bookshare has learned that this book offers only partial accessibility. We have kept it in the collection because it is useful for some of our members. To explore further access options with us, please contact us through the Book Quality link on the right sidebar. Benetech is actively working on projects to improve accessibility issues such as these.
Think Bayes: Bayesian Statistics In Python
by Allen B. DowneyIf you know how to program, you're ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical formulas, using discrete probability distributions rather than continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer and you'll begin to apply these techniques to real-world problems.Bayesian statistical methods are becoming more common and more important, but there aren't many resources available to help beginners. Based on undergraduate classes taught by author Allen B. Downey, this book's computational approach helps you get a solid start.Use your programming skills to learn and understand Bayesian statisticsWork with problems involving estimation, prediction, decision analysis, evidence, and Bayesian hypothesis testingGet started with simple examples, using coins, dice, and a bowl of cookiesLearn computational methods for solving real-world problems
Think Complexity
by Allen B. DowneyExpand your Python skills by working with data structures and algorithms in a refreshing context--through an eye-opening exploration of complexity science. Whether you're an intermediate-level Python programmer or a student of computational modeling, you'll delve into examples of complex systems through a series of exercises, case studies, and easy-to-understand explanations. You'll work with graphs, algorithm analysis, scale-free networks, and cellular automata, using advanced features that make Python such a powerful language. Ideal as a text for courses on Python programming and algorithms, Think Complexity will also help self-learners gain valuable experience with topics and ideas they might not encounter otherwise. Work with NumPy arrays and SciPy methods, basic signal processing and Fast Fourier Transform, and hash tables Study abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machines Get starter code and solutions to help you re-implement and extend original experiments in complexity Explore the philosophy of science, including the nature of scientific laws, theory choice, realism and instrumentalism, and other topics Examine case studies of complex systems submitted by students and readers
Think Data Structures: Algorithms and Information Retrieval in Java
by Allen B. DowneyIf you’re a student studying computer science or a software developer preparing for technical interviews, this practical book will help you learn and review some of the most important ideas in software engineering—data structures and algorithms—in a way that’s clearer, more concise, and more engaging than other materials.By emphasizing practical knowledge and skills over theory, author Allen Downey shows you how to use data structures to implement efficient algorithms, and then analyze and measure their performance. You’ll explore the important classes in the Java collections framework (JCF), how they’re implemented, and how they’re expected to perform. Each chapter presents hands-on exercises supported by test code online.Use data structures such as lists and maps, and understand how they workBuild an application that reads Wikipedia pages, parses the contents, and navigates the resulting data treeAnalyze code to predict how fast it will run and how much memory it will requireWrite classes that implement the Map interface, using a hash table and binary search treeBuild a simple web search engine with a crawler, an indexer that stores web page contents, and a retriever that returns user query resultsOther books by Allen Downey include Think Java, Think Python, Think Stats, and Think Bayes.
Think Python: How To Think Like A Computer Scientist
by Allen B. DowneyIf you want to learn how to program, working with Python is an excellent way to start. This hands-on guide takes you through the language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. This second edition and its supporting code have been updated for Python 3.Through exercises in each chapter, youâ??ll try out programming concepts as you learn them. Think Python is ideal for students at the high school or college level, as well as self-learners, home-schooled students, and professionals who need to learn programming basics. Beginners just getting their feet wet will learn how to start with Python in a browser.Start with the basics, including language syntax and semanticsGet a clear definition of each programming conceptLearn about values, variables, statements, functions, and data structures in a logical progressionDiscover how to work with files and databasesUnderstand objects, methods, and object-oriented programmingUse debugging techniques to fix syntax, runtime, and semantic errorsExplore interface design, data structures, and GUI-based programs through case studies
Think Python: How To Think Like A Computer Scientist
by Allen B. DowneyPython is an excellent way to get started in programming, and this clear, concise guide walks you through Python a step at a time—beginning with basic programming concepts before moving on to functions, data structures, and object-oriented design. This revised third edition reflects the growing role of large language models (LLMs) in programming and includes exercises on effective LLM prompts, testing code, and debugging skills.With this popular hands-on guide at your side, you'll get:A grounding in the syntax and semantics of the Python languageA clear definition of each programming concept, with emphasis on clear vocabularyHow to work with variables, statements, functions, and data structures in a logical progressionTechniques for reading and writing files and databasesA solid understanding of objects, methods, and object-oriented programmingDebugging strategies for syntax, runtime, and semantic errorsAn introduction to recursion, interface design, data structures, and basic algorithmsHow to use LLMs—including effective prompts, testing code, and debuggingAnd more
Think Stats
by Allen B. DowneyIf you know how to program, you have the skills to turn data into knowledge using the tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. You'll work with a case study throughout the book to help you learn the entire data analysis process--from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts. Develop your understanding of probability and statistics by writing and testing code Run experiments to test statistical behavior, such as generating samples from several distributions Use simulations to understand concepts that are hard to grasp mathematically Learn topics not usually covered in an introductory course, such as Bayesian estimation Import data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics tools Use statistical inference to answer questions about real-world data
Think Stats: Exploratory Data Analysis
by Allen B. DowneyIf you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.By working with a single case study throughout this thoroughly revised book, you’ll learn the entire process of exploratory data analysis—from collecting data and generating statistics to identifying patterns and testing hypotheses. You’ll explore distributions, rules of probability, visualization, and many other tools and concepts.New chapters on regression, time series analysis, survival analysis, and analytic methods will enrich your discoveries.Develop an understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyImport data from most sources with Python, rather than rely on data that’s cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data
Think Julia: How to Think Like a Computer Scientist
by Allen B. Downey Ben LauwensIf you’re just learning how to program, Julia is an excellent JIT-compiled, dynamically-typed language with a clean syntax. This hands-on guide uses Julia (version 1.0) to walk you through programming one step at a time, beginning with basic programming concepts before moving on to more advanced capabilities, such as creating new types and multiple dispatch.Designed from the beginning for high performance, Julia is a general-purpose language not only ideal for numerical analysis and computational science, but also for web programming or scripting. Through exercises in each chapter, you’ll try out programming concepts as you learn them.Think Julia is ideal for students at the high school or college level, as well as self-learners, home-schooled students, and professionals who need to learn programming basics.Start with the basics, including language syntax and semanticsGet a clear definition of each programming conceptLearn about values, variables, statements, functions, and data structures in a logical progressionDiscover how to work with files and databasesUnderstand types, methods, and multiple dispatchUse debugging techniques to fix syntax, runtime, and semantic errorsExplore interface design and data structures through case studies
Think Java: How to Think Like a Computer Scientist
by Allen B. Downey Chris MayfieldCurrently used at many colleges, universities, and high schools, this hands-on introduction to computer science is ideal for people with little or no programming experience. The goal of this concise book is not just to teach you Java, but to help you think like a computer scientist. You'll learn how to program--a useful skill by itself--but you'll also discover how to use programming as a means to an end.Authors Allen Downey and Chris Mayfield start with the most basic concepts and gradually move into topics that are more complex, such as recursion and object-oriented programming. Each brief chapter covers the material for one week of a college course and includes exercises to help you practice what you've learned.Learn one concept at a time: tackle complex topics in a series of small steps with examplesUnderstand how to formulate problems, think creatively about solutions, and write programs clearly and accuratelyDetermine which development techniques work best for you, and practice the important skill of debuggingLearn relationships among input and output, decisions and loops, classes and methods, strings and arraysWork on exercises involving word games, graphics, puzzles, and playing cards
Think Java: How to Think Like a Computer Scientist
by Allen B. Downey Chris MayfieldCurrently used at many colleges, universities, and high schools, this hands-on introduction to computer science is ideal for people with little or no programming experience. The goal of this concise book is not just to teach you Java, but to help you think like a computer scientist. You’ll learn how to program—a useful skill by itself—but you’ll also discover how to use programming as a means to an end.Authors Allen Downey and Chris Mayfield start with the most basic concepts and gradually move into topics that are more complex, such as recursion and object-oriented programming. Each brief chapter covers the material for one week of a college course and includes exercises to help you practice what you’ve learned.Learn one concept at a time: tackle complex topics in a series of small steps with examplesUnderstand how to formulate problems, think creatively about solutions, and write programs clearly and accuratelyDetermine which development techniques work best for you, and practice the important skill of debuggingLearn relationships among input and output, decisions and loops, classes and methods, strings and arraysWork on exercises involving word games, graphics, puzzles, and playing cardsThe updated second edition of Think Java also features new chapters on polymorphism and data processing, as well as content covering changes through Java 12.
Think Perl 6: How to Think Like a Computer Scientist
by Allen B. Downey Laurent RosenfeldWant to learn how to program and think like a computer scientist? This practical guide gets you started on your programming journey with the help of Perl 6, the younger sister of the popular Perl programming language. Ideal for beginners, this hands-on book includes over 100 exercises with multiple solutions, and more than 1,000 code examples so you can quickly practice what you learn. Experienced programmers—especially those who know Perl 5—will also benefit.Divided into two parts, Think Perl 6 starts with basic concepts that every programmer needs to know, and then focuses on different programming paradigms and some more advanced programming techniques. With two semesters’ worth of lessons, this book is the perfect teaching tool for computer science beginners in colleges and universities.Learn basic concepts including variables, expressions, statements, functions, conditionals, recursion, and loopsUnderstand commonly used basic data structures and the most useful algorithmsDive into object-oriented programming, and learn how to construct your own types and methods to extend the languageUse grammars and regular expressions to analyze textual contentExplore how functional programming can help you make your code simpler and more expressive
Practical Swift
by Eric DowneyTake a firsthand tour of Xcode and all the latest features Swift 3 has to offer. If you have picked up this book, chances are you know a little bit about Swift Programming. With Practical Swift you'll develop an advanced understanding of the language that will enable you to create a reference guide using Xcode Playgrounds, one you can continue to grow throughout your iOS career. This book not only shows you how to code in a clean and concise manner, but also the why behind the code. Understanding why will be instrumental in your advancement as a Swift developer. What You'll learn: Review the evolution of Swift and the latest features in Swift 3 Study architecture and design patterns Examine Protocol Oriented Programming Understand Swift generics Test Swift code Build an iOS App with core data from scratch Who This Book Is For: The primary audience for this book is developers who have started learning iOS and Swift and want to learn more of the intermediate to advanced topics available in Swift. The secondary audience is developers who have experience in iOS and Swift and want a good reference book for concepts they might already know, but are looking to re-enforce.
Turing's Legacy: Developments from Turing's Ideas in Logic
by Rod DowneyAlan Turing was an inspirational figure who is now recognised as a genius of modern mathematics. In addition to leading the Allied forces' code-breaking effort at Bletchley Park in World War II, he proposed the theoretical foundations of modern computing and anticipated developments in areas from information theory to computer chess. His ideas have been extraordinarily influential in modern mathematics and this book traces such developments by bringing together essays by leading experts in logic, artificial intelligence, computability theory and related areas. Together, they give insight into this fascinating man, the development of modern logic, and the history of ideas. The articles within cover a diverse selection of topics, such as the development of formal proof, differing views on the Church–Turing thesis, the development of combinatorial group theory, and Turing's work on randomness which foresaw the ideas of algorithmic randomness that would emerge many years later.
Fundamentals of Parameterized Complexity
by Rodney G. Downey Michael R. FellowsThis comprehensive and self-contained textbook presents an accessible overview of the state of the art of multivariate algorithmics and complexity. Increasingly, multivariate algorithmics is having significant practical impact in many application domains, with even more developments on the horizon. The text describes how the multivariate framework allows an extended dialog with a problem, enabling the reader who masters the complexity issues under discussion to use the positive and negative toolkits in their own research. Features: describes many of the standard algorithmic techniques available for establishing parametric tractability; reviews the classical hardness classes; explores the various limitations and relaxations of the methods; showcases the powerful new lower bound techniques; examines various different algorithmic solutions to the same problems, highlighting the insights to be gained from each approach; demonstrates how complexity methods and ideas have evolved over the past 25 years.
Guide to Web Development with Java: Understanding Website Creation (Texts in Computer Science)
by Tim DowneyThis comprehensive Guide to Web Development with Java introduces the readers to the three-tiered, Model-View-Controller architecture by using Spring JPA, JSPs, and Spring MVC controllers. These three technologies use Java, so that a student with a background in programming will be able to master them with ease, with the end result of being able to create web applications that use MVC, validate user input,and save data to a database.Topics and features:• Presents web development topics in an accessible, easy-to-follow style, focusing on core information first, and allowing the reader to gain basic understanding before moving forwards• Contains many helpful pedagogical tools for students and lecturers, such as questions and exercises at the end of each chapter, detailed illustrations, chapter summaries, and a glossary• Uses existing powerful technologies that are freely available on the web to speed up web development, such as Spring Boot, Spring MVC, Spring JPA, Hibernate, JSP, JSTL, and Java 1.8• Discusses HTML, HTML forms, and Cascading Style Sheets• Starts with the simplest technology for web development (JSP) and gradually introduces the reader to more complex topics• Introduces core technologies from the outset, such as the Model-View-Controller architecture• Includes examples for accessing common web services• Provides supplementary examples and tutorials
Guide to Web Development with Java
by Tim DowneyThis comprehensive textbook introduces readers to the three-tiered, Model-View-Controller (MVC) architecture by using Hibernate, JSPs, and Java Servlets. These three technologies all use Java, so that a student with a background in programming will be able to master them with ease, with the end result of being able to create web applications that use MVC, validate user input and save data to a database. Features: presents the many topics of web development in small steps, in an accessible, easy-to-follow style; uses powerful technologies that are freely available on the web to speed up web development, such as JSP, JavaBeans, annotations, JSTL, Java 1.5, Hibernate and Tomcat; discusses HTML, HTML Forms, Cascading Style Sheets and XML; introduces core technologies from the outset, such as the MVC architecture; contains questions and exercises at the end of each chapter, detailed illustrations, chapter summaries, and a glossary; includes examples for accessing common web services.
Gradient Expectations: Structure, Origins, and Synthesis of Predictive Neural Networks
by Keith L. DowningAn insightful investigation into the mechanisms underlying the predictive functions of neural networks—and their ability to chart a new path for AI.Prediction is a cognitive advantage like few others, inherently linked to our ability to survive and thrive. Our brains are awash in signals that embody prediction. Can we extend this capability more explicitly into synthetic neural networks to improve the function of AI and enhance its place in our world? Gradient Expectations is a bold effort by Keith L. Downing to map the origins and anatomy of natural and artificial neural networks to explore how, when designed as predictive modules, their components might serve as the basis for the simulated evolution of advanced neural network systems.Downing delves into the known neural architecture of the mammalian brain to illuminate the structure of predictive networks and determine more precisely how the ability to predict might have evolved from more primitive neural circuits. He then surveys past and present computational neural models that leverage predictive mechanisms with biological plausibility, identifying elements, such as gradients, that natural and artificial networks share. Behind well-founded predictions lie gradients, Downing finds, but of a different scope than those that belong to today&’s deep learning. Digging into the connections between predictions and gradients, and their manifestation in the brain and neural networks, is one compelling example of how Downing enriches both our understanding of such relationships and their role in strengthening AI tools. Synthesizing critical research in neuroscience, cognitive science, and connectionism, Gradient Expectations offers unique depth and breadth of perspective on predictive neural-network models, including a grasp of predictive neural circuits that enables the integration of computational models of prediction with evolutionary algorithms.
Logic And Declarative Language
by M. DownwardLogic has acquired a reputation for difficulty, perhaps because many of the approaches adopted have been more suitable for mathematicians than computer scientists. This book shows that the subject is not inherently difficult and that the connections between logic and declarative language are straightforward. Many exercises have been included in the hope that these will lead to a much greater confidence in manual proofs, therefore leading to a greater confidence in automated proofs.
Practical Automation with PowerShell
by Matthew DowstTake PowerShell beyond simple scripts and build time-saving automations for your team, your users, and the world.In Practical Automation with PowerShell you will learn how to: Build PowerShell functions to automate common and complex tasks Create smart automations that are adaptable to new challenges Structure your code for sharing and reusability Store and secure your automations Execute automations with Azure Automation, Jenkins, Task Scheduler, and Cron Share your automations with your team and non-technical colleagues Store and retrieve data, credentials, and variables Use source control solutions to maintain and test code changes Provide front-end UI solutions for PowerShell automations Practical Automation in PowerShell reveals how you can use PowerShell to build automation solutions for a huge number of common admin and DevOps tasks. Author Matthew Dowst uses his decades of experience to lay out a real blueprint for setting up an enterprise scripting environment with PowerShell. The book goes beyond the basics to show you how to handle the unforeseen complexities that can keep automations from becoming reusable and resilient. From the console to the cloud, you'll learn how to manage your code, avoid common pitfalls, and create sharable automations that are adaptable to different use cases. About the Technology The PowerShell scripting language is a force multiplier, giving you programmatic control over your whole data center. With this powerful tool, you can create reusable automations that radically improve consistency and productivity on your Ops team. This book shows you how to design, write, organize, and deploy scripts to automate operations on systems of all sizes, from local servers to enterprise clusters in the cloud. About the Book Practical Automation with PowerShell: Effective scripting from the console to the cloud shows you how to build PowerShell automations for local and cloud systems. In it, you&’ll find tips for identifying automatable tasks, techniques for structuring and managing scripts, and lots of well-explained example code. You&’ll even learn how to adapt existing scripts to new use cases and empower non-technical users through easy-to-understand SharePoint frontends. What&’s Inside Structure PowerShell code for sharing and reusability Store and secure your automations Execute automation with Azure Automation, Jenkins, Task Scheduler, and Cron Store and retrieve data, credentials, and variables Use source control solutions to maintain and test code changes About the Reader For sysadmin and IT professionals who manage backend systems. About the Author Matthew Dowst has over 15 years of experience in IT management and consulting. Table of contents PART 1 1 PowerShell automation 2 Get started automating PART 2 3 Scheduling automation scripts 4 Handling sensitive data 5 PowerShell remote execution 6 Making adaptable automations 7 Working with SQL 8 Cloud-based automation 9 Working outside of PowerShell 10 Automation coding best practices PART 3 11 End-user scripts and forms 12 Sharing scripts among a team 13 Testing your scripts 14 Maintaining your code
Introducing Go
by Caleb DoxseyPerfect for beginners familiar with programming basics, this hands-on guide provides an easy introduction to Go, the general-purpose programming language from Google. Author Caleb Doxsey covers the language's core features with step-by-step instructions and exercises in each chapter to help you practice what you learn.Go is a general-purpose programming language with a clean syntax and advanced features, including concurrency. This book provides the one-on-one support you need to get started with the language, with short, easily digestible chapters that build on one another. By the time you finish this book, not only will you be able to write real Go programs, you'll be ready to tackle advanced techniques.Jump into Go basics, including data types, variables, and control structuresLearn complex types, such as slices, functions, structs, and interfacesExplore Go's core library and learn how to create your own packageWrite tests for your code by using the language's go test programLearn how to run programs concurrently with goroutines and channelsGet suggestions to help you master the craft of programming
C# Programming: From Problem Analysis to Program Design
by Barbara DoyleOnly Doyle's C# PROGRAMMING: FROM PROBLEM ANALYSIS TO PROGRAM DESIGN, 4E brilliantly balances today's most important programming principles and concepts with the latest insights into C#. This perfect introductory book highlights the latest Visual Studio 2012 and C# 4. 0 with a unique, principles-based approach to give readers a deep understanding of programming. You'll find just the right amount of detail to create an important foundation in programming. This edition's straightforward approach and understandable vocabulary make it easier for readers to grasp new programming concepts without distraction. The book introduces a variety of fundamental programming concepts, from data types and expressions to arrays and collections, all using the popular C# language. New programming exercises and new numbered examples throughout this edition reflect the latest updates in Visual Studio 2012, while learning objectives, case studies and Coding Standards summaries in each chapter ensure mastery. While the book assumes no prior programming knowledge, coverage extends beyond traditional books to cover new advanced topics, such as portable class libraries used to create applications for Windows Phone and other platforms.
What Does it Mean to be Human? Life, Death, Personhood and the Transhumanist Movement (Anticipation Science #3)
by D. John DoyleThis book is a critical examination of the philosophical and moral issues in relation to human enhancement and the various related medical developments that are now rapidly moving from the laboratory into the clinical realm. In the book, the author critically examines technologies such as genetic engineering, neural implants, pharmacologic enhancement, and cryonic suspension from transhumanist and bioconservative positions, focusing primarily on moral issues and what it means to be a human in a setting where technological interventions sometimes impact strongly on our humanity. The author also introduces the notion that death is a process rather than an event, as well as identifies philosophical and clinical limitations in the contemporary determination of brain death as a precursor to organ procurement for transplantation. The discussion on what exactly it means to be dead is later applied to explore philosophical and clinical issues germane to the cryonics movement. Written by a physician/ scientist and heavily referenced to the peer-reviewed medical and scientific literature, the book is aimed at advanced students and academics but should be readable by any intelligent reader willing to carry out some side-reading. No prior knowledge of moral philosophy is assumed, as the various key approaches to moral philosophy are outlined early in the book.
Beginning PHP 5.3
by Matt DoyleThis book is intended for anyone starting out with PHP programming. If you've previously worked in another programming language such as Java, C#, or Perl, you'll probably pick up the concepts in the earlier chapters quickly; however, the book assumes no prior experience of programming or of building Web applications. That said, because PHP is primarily a Web technology, it will help if you have at least some knowledge of other Web technologies, particularly HTML and CSS. Many Web applications make use of a database to store data, and this book contains three chapters on working with MySQL databases. Once again, if you're already familiar with databases in general -- and MySQL in particular -- you'll be able to fly through these chapters. However, even if you've never touched a database before in your life, you should still be able to pick up a working knowledge by reading through these chapters.