The authors have taken the mystery out of complex queries and explained principles and techniques with such clarity that a "Mere Mortal" will indeed be empowered to perform the superhuman. Do not walk past this book "--Graham Mandeno, Database Consultant""SQL Queries for Mere Mortals" provides a step-by-step, easy-to-read introduction to writing SQL queries. It includes hundreds of examples with detailed explanations. This book provides the tools you need to understand, modify, and create SQL queries"--Keith W. Hare, Convenor, ISO/IEC JTC1 SC32 WG3--the International SQL Standards Committee"I learned SQL primarily from the first edition of this book, and I am pleased to see a second edition of this book so that others can continue to benefit from its organized presentation of the language. Starting from how to design your tables so that SQL can be effective (a common problem for database beginners), and then continuing through the various aspects of SQL construction and capabilities, the reader can become a moderate expert upon completing the book and its samples. Learning how to convert a question in English into a meaningful SQL statement will greatly facilitate your mastery of the language. Numerous examples from real life will help you visualize how to use SQL to answer the questions about the data in your database. Just one of the "watch out for this trap" items will save you more than the cost of the book when you avoid that problem when writing your queries. I highly recommend this book if you want to tap the full potential of your database."--Kenneth D. Snell, Ph.D., Database Designer/Programmer"I don't think they do this in public schools any more, and it is a shame, but do you remember in the seventh and eighth grades when you learned to diagram a sentence? Those of you who do may no longer remember how you did it, but all of you do write better sentences because of it. John Viescas and Mike Hernandez must have remembered because they take everyday English queries and literally translate them into SQL. This is an important book for all database designers. It takes the complexity of mathematical Set Theory and of First Order Predicate Logic, as outlined in E. F. Codd's original treatise on relational database design, and makes it easy for anyone to understand. If you want an elementary- through intermediate-level course on SQL, this is the one book that is a requirement, no matter how many others you buy."--Arvin Meyer, MCP, MVP"Even in this day of wizards and code generators, successful database developers still require a sound knowledge of Structured Query Language (SQL, the standard language for communicating with most database systems). In this book, John and Mike do a marvelous job of making what's usually a dry and difficult subject come alive, presenting the material with humor in a logical manner, with plenty of relevant examples. I would say that this book should feature prominently in the collection on the bookshelf of all serious developers, except that I'm sure it'll get so much use that it won't spend much time on the shelf "-- Doug Steele, Microsoft Access Developer and author"Over the last several decades, SQL has evolved from a language known only to computer specialists to a widely used international standard of the computer industry. The number of new applications deployed each year using SQL now totals in the millions. If you are accessing corporate information from the Internet or from an internal network, you are probably using SQL. This new edition of "SQL Queries for Mere Mortals" helps new users learn the foundations of SQL queries, and is an essential reference guide for intermediate and advanced users.The accompanying CD contains five sample databases used for the example queries throughout the book in four different formats: Microsoft SQL Server 2000 and later, Microsoft Access 2000 and later, MySQL version 5.0 and later, and SQL scripts that can be used with most other implementations of the language.

    Not to worry: This book is the one place you can turn to find quick, non-intimidating, excellent design help. In The Non-Designer's Design Book, 2nd Edition, best-selling author Robin Williams turns her attention to the basic principles of good design and typography. All you have to do is follow her clearly explained concepts, and you'll begin producing more sophisticated, professional, and interesting pages immediately. Humor-infused, jargon-free prose interspersed with design exercises, quizzes, illustrations, and dozens of examples make learning a snap—which is just what audiences have come to expect from this best-selling author.

    Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data

    I loved the tutorial-style game-like program development. This book rekindled my earliest joys of programming. Plus, JavaScript!" —Brendan Eich, creator of JavaScriptJavaScript is the language of the Web, and it's at the heart of every modern website from the lowliest personal blog to the mighty Google Apps. Though it's simple for beginners to pick up and play with, JavaScript is not a toy—it's a flexible and complex language, capable of much more than the showy tricks most programmers use it for.Eloquent JavaScript goes beyond the cut-and-paste scripts of the recipe books and teaches you to write code that's elegant and effective. You'll start with the basics of programming, and learn to use variables, control structures, functions, and data structures. Then you'll dive into the real JavaScript artistry: higher-order functions, closures, and object-oriented programming.Along the way you'll learn to:Master basic programming techniques and best practices Harness the power of functional and object-oriented programming Use regular expressions to quickly parse and manipulate strings Gracefully deal with errors and browser incompatibilities Handle browser events and alter the DOM structure Most importantly, Eloquent JavaScript will teach you to express yourself in code with precision and beauty. After all, great programming is an art, not a science—so why settle for a killer app when you can create a masterpiece?

    Weinberg adds new insights and highlights the similarities and differences between now and then. Using a conversational style that invites the reader to join him, Weinberg reunites with some of his most insightful writings on the human side of software engineering.Topics include egoless programming, intelligence, psychological measurement, personality factors, motivation, training, social problems on large projects, problem-solving ability, programming language design, team formation, the programming environment, and much more.Dorset House Publishing is proud to make this important text available to new generations of programmers -- and to encourage readers of the first edition to return to its valuable lessons.

     Data Structures and Algorithms in Python is the first mainstream object-oriented book available for the Python data structures course. Designed to provide a comprehensive introduction to data structures and algorithms, including their design, analysis, and implementation, the text will maintain the same general structure as Data Structures and Algorithms in Java and Data Structures and Algorithms in C++.

    Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics.An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

    By following the recommendations of the Association of Computing Machinery's Java Task Force, this first edition text adopts a modern objects-first approach that introduces readers to useful hierarchies from the very beginning.KEY TOPICS: Introduction; Programming by Example; Expressions; Statement Forms; Methods; Objects and Classes; Objects and Memory; Strings and Characters; Object-Oriented Graphics; Event-Driven Programs; Arrays and ArrayLists; Searching and Sorting; Collection Classes; Looking Ahead.MARKET: A modern objects-first approach to the Java programming language that introduces readers to useful class hierarchies from the very beginning.

    Many examples are taken from real-world projects. The book focuses on high-level design as well as the gritty details of the Python syntax. The provided exercises inspire the reader to think about his or her own code, rather than providing solved problems. If you're new to Object Oriented Programming techniques, or if you have basic Python skills and wish to learn in depth how and when to correctly apply Object Oriented Programming in Python, this is the book for you. If you are an object-oriented programmer for other languages, you too will find this book a useful introduction to Python, as it uses terminology you are already familiar with. Python 2 programmers seeking a leg up in the new world of Python 3 will also find the book beneficial, and you need not necessarily know Python 2.

    By staying current, remaining relevant, and adapting to emerging course needs, this market-leading text has continued to define the operating systems course. This Seventh Edition not only presents the latest and most relevant systems, it also digs deeper to uncover those fundamental concepts that have remained constant throughout the evolution of today's operation systems. With this strong conceptual foundation in place, students can more easily understand the details related to specific systems. New Adaptations * Increased coverage of user perspective in Chapter 1. * Increased coverage of OS design throughout. * A new chapter on real-time and embedded systems (Chapter 19). * A new chapter on multimedia (Chapter 20). * Additional coverage of security and protection. * Additional coverage of distributed programming. * New exercises at the end of each chapter. * New programming exercises and projects at the end of each chapter. * New student-focused pedagogy and a new two-color design to enhance the learning process.

    If you're a reasonably proficient programmer who can think logically, you have all the background you'll need. Stepanov and Rose introduce the relevant abstract algebra and number theory with exceptional clarity. They carefully explain the problems mathematicians first needed to solve, and then show how these mathematical solutions translate to generic programming and the creation of more effective and elegant code. To demonstrate the crucial role these mathematical principles play in many modern applications, the authors show how to use these results and generalized algorithms to implement a real-world public-key cryptosystem. As you read this book, you'll master the thought processes necessary for effective programming and learn how to generalize narrowly conceived algorithms to widen their usefulness without losing efficiency. You'll also gain deep insight into the value of mathematics to programming--insight that will prove invaluable no matter what programming languages and paradigms you use. You will learn aboutHow to generalize a four thousand-year-old algorithm, demonstrating indispensable lessons about clarity and efficiencyAncient paradoxes, beautiful theorems, and the productive tension between continuous and discreteA simple algorithm for finding greatest common divisor (GCD) and modern abstractions that build on itPowerful mathematical approaches to abstractionHow abstract algebra provides the idea at the heart of generic programmingAxioms, proofs, theories, and models: using mathematical techniques to organize knowledge about your algorithms and data structuresSurprising subtleties of simple programming tasks and what you can learn from themHow practical implementations can exploit theoretical knowledge

    But building a machine learning system requires that you make practical decisions: Should you collect more training data? Should you use end-to-end deep learning? How do you deal with your training set not matching your test set? and many more. Historically, the only way to learn how to make these "strategy" decisions has been a multi-year apprenticeship in a graduate program or company. This is a book to help you quickly gain this skill, so that you can become better at building AI systems.

    Instead of relying on another attacker's tools, this book will teach you to forge your own weapons using the Python programming language. This book demonstrates how to write Python scripts to automate large-scale network attacks, extract metadata, and investigate forensic artifacts. It also shows how to write code to intercept and analyze network traffic using Python, craft and spoof wireless frames to attack wireless and Bluetooth devices, and how to data-mine popular social media websites and evade modern anti-virus.

    But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications.Authors Jeremy Howard and Sylvain Gugger show you how to train a model on a wide range of tasks using fastai and PyTorch. You'll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes.Train models in computer vision, natural language processing, tabular data, and collaborative filteringLearn the latest deep learning techniques that matter most in practiceImprove accuracy, speed, and reliability by understanding how deep learning models workDiscover how to turn your models into web applicationsImplement deep learning algorithms from scratchConsider the ethical implications of your work

    Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyze sample datasets and write simple machine learning algorithms. "Machine Learning for Hackers" is ideal for programmers from any background, including business, government, and academic research.Develop a naive Bayesian classifier to determine if an email is spam, based only on its textUse linear regression to predict the number of page views for the top 1,000 websitesLearn optimization techniques by attempting to break a simple letter cipherCompare and contrast U.S. Senators statistically, based on their voting recordsBuild a "whom to follow" recommendation system from Twitter data